Image/text automatic indexing and retrieval system using context vector approach

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Caid, William R.; Ren, Clara Z.; McCabe, Patrick

1995-11-01

Thousands of documents and images are generated daily both on and off line on the information superhighway and other media. Storage technology has improved rapidly to handle these data but indexing this information is becoming very costly. HNC Software Inc. has developed a technology for automatic indexing and retrieval of free text and images. This technique is demonstrated and is based on the concept of `context vectors' which encode a succinct representation of the associated text and features of sub-image. In this paper, we will describe the Automated Librarian System which was designed for free text indexing and the Image Content Addressable Retrieval System (ICARS) which extends the technique from the text domain into the image domain. Both systems have the ability to automatically assign indices for a new document and/or image based on the content similarities in the database. ICARS also has the capability to retrieve images based on similarity of content using index terms, text description, and user-generated images as a query without performing segmentation or object recognition.

Comparison of Document Index Graph Using TextRank and HITS Weighting Method in Automatic Text Summarization

NASA Astrophysics Data System (ADS)

Hadyan, Fadhlil; Shaufiah; Arif Bijaksana, Moch.

2017-01-01

Automatic summarization is a system that can help someone to take the core information of a long text instantly. The system can help by summarizing text automatically. there’s Already many summarization systems that have been developed at this time but there are still many problems in those system. In this final task proposed summarization method using document index graph. This method utilizes the PageRank and HITS formula used to assess the web page, adapted to make an assessment of words in the sentences in a text document. The expected outcome of this final task is a system that can do summarization of a single document, by utilizing document index graph with TextRank and HITS to improve the quality of the summary results automatically.

Unsupervised Medical Entity Recognition and Linking in Chinese Online Medical Text

PubMed Central

Gan, Liang; Cheng, Mian; Wu, Quanyuan

2018-01-01

Online medical text is full of references to medical entities (MEs), which are valuable in many applications, including medical knowledge-based (KB) construction, decision support systems, and the treatment of diseases. However, the diverse and ambiguous nature of the surface forms gives rise to a great difficulty for ME identification. Many existing solutions have focused on supervised approaches, which are often task-dependent. In other words, applying them to different kinds of corpora or identifying new entity categories requires major effort in data annotation and feature definition. In this paper, we propose unMERL, an unsupervised framework for recognizing and linking medical entities mentioned in Chinese online medical text. For ME recognition, unMERL first exploits a knowledge-driven approach to extract candidate entities from free text. Then, the categories of the candidate entities are determined using a distributed semantic-based approach. For ME linking, we propose a collaborative inference approach which takes full advantage of heterogenous entity knowledge and unstructured information in KB. Experimental results on real corpora demonstrate significant benefits compared to recent approaches with respect to both ME recognition and linking. PMID:29849994

Our journey to digital curation of the Jeghers Medical Index

PubMed Central

Gawdyda, Lori; Carter, Kimbroe; Willson, Mark; Bedford, Denise

2017-01-01

Background Harold Jeghers, a well-known medical educator of the twentieth century, maintained a print collection of about one million medical articles from the late 1800s to the 1990s. This case study discusses how a print collection of these articles was transformed to a digital database. Case Presentation Staff in the Jeghers Medical Index, St. Elizabeth Youngstown Hospital, converted paper articles to Adobe portable document format (PDF)/A-1a files. Optical character recognition was used to obtain searchable text. The data were then incorporated into a specialized database. Lastly, articles were matched to PubMed bibliographic metadata through automation and human review. An online database of the collection was ultimately created. The collection was made part of a discovery search service, and semantic technologies have been explored as a method of creating access points. Conclusions This case study shows how a small medical library made medical writings of the nineteenth and twentieth centuries available in electronic format for historic or semantic research, highlighting the efficiencies of contemporary information technology. PMID:28670213

Our journey to digital curation of the Jeghers Medical Index.

PubMed

Gawdyda, Lori; Carter, Kimbroe; Willson, Mark; Bedford, Denise

2017-07-01

Harold Jeghers, a well-known medical educator of the twentieth century, maintained a print collection of about one million medical articles from the late 1800s to the 1990s. This case study discusses how a print collection of these articles was transformed to a digital database. Staff in the Jeghers Medical Index, St. Elizabeth Youngstown Hospital, converted paper articles to Adobe portable document format (PDF)/A-1a files. Optical character recognition was used to obtain searchable text. The data were then incorporated into a specialized database. Lastly, articles were matched to PubMed bibliographic metadata through automation and human review. An online database of the collection was ultimately created. The collection was made part of a discovery search service, and semantic technologies have been explored as a method of creating access points. This case study shows how a small medical library made medical writings of the nineteenth and twentieth centuries available in electronic format for historic or semantic research, highlighting the efficiencies of contemporary information technology.

Comparison of indexing times among articles from medical, nursing, and pharmacy journals.

PubMed

Rodriguez, Ryan W

2016-04-15

Results of an analysis of the times to indexing of articles published in medical, nursing, and pharmacy journals are reported. MEDLINE data were retrieved for articles published in selected general practice medical, nursing, and pharmacy journals and entered into the PubMed system in 2012 and 2013. Collected data included PubMed entry date, date of indexing with Medical Subject Headings (MeSH) terms, and publication characteristics. Survival analysis was performed to assess the primary outcome of time to indexing. Cox proportional hazards models were developed to assess the effect of healthcare discipline and source journal on the primary outcome. Data were collected for 19,259 articles, of which 78.7%, 12.6%, and 8.7% originated from medical, nursing, and pharmacy journals, respectively. For medical, pharmacy, and nursing journals, 97.8%, 90.8%, and 50.1% of articles, respectively, were indexed within one year of PubMed entry; the corresponding median (interquartile range) times to indexing were 52 (20-68), 186 (150-246), and 252 (168-301) days. Unadjusted hazard ratios derived from Cox models indicated that indexing within one year was significantly less likely for articles published in pharmacy or nursing journals versus medical journals and for articles from all evaluated journals versus a designated reference publication (New England Journal of Medicine). Analysis of major medical, nursing, and pharmacy journals found that articles from nursing and pharmacy journals were indexed with MeSH terms more slowly than articles from medical journals. Journal identity was significantly associated with time to indexing. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Automated assessment of medical training evaluation text.

PubMed

Zhang, Rui; Pakhomov, Serguei; Gladding, Sophia; Aylward, Michael; Borman-Shoap, Emily; Melton, Genevieve B

2012-01-01

Medical post-graduate residency training and medical student training increasingly utilize electronic systems to evaluate trainee performance based on defined training competencies with quantitative and qualitative data, the later of which typically consists of text comments. Medical education is concomitantly becoming a growing area of clinical research. While electronic systems have proliferated in number, little work has been done to help manage and analyze qualitative data from these evaluations. We explored the use of text-mining techniques to assist medical education researchers in sentiment analysis and topic analysis of residency evaluations with a sample of 812 evaluation statements. While comments were predominantly positive, sentiment analysis improved the ability to discriminate statements with 93% accuracy. Similar to other domains, Latent Dirichlet Analysis and Information Gain revealed groups of core subjects and appear to be useful for identifying topics from this data.

A bibliometric analysis of evaluative medical education studies: characteristics and indexing accuracy.

PubMed

Sampson, Margaret; Horsley, Tanya; Doja, Asif

2013-03-01

To determine the characteristics of medical education studies published in general and internal medicine (GIM) and medical education journals, and to analyze the accuracy of their indexing. The authors identified the five GIM and five medical education journals that published the most articles indexed in MEDLINE as medical education during January 2001 to January 2010. They searched Ovid MEDLINE for evaluative medical education studies published in these journals during this period and classified them as quantitative or qualitative studies according to MEDLINE indexing. They also examined themes and learner levels targeted. Using a random sample of records, they assessed the accuracy of study-type indexing. Of 4,418 records retrieved, 3,853 (87.2%) were from medical education journals and 565 (12.3%) were from GIM journals. Qualitative studies and program evaluations were more prevalent within medical education journals, whereas GIM journals published a higher proportion of clinical trials and systematic reviews (χ=74.28, df=3, P<.001). Medical education journals had a concentration of studies targeting medical students, whereas GIM journals had a concentration targeting residents; themes were similar. The authors confirmed that 170 (56.7%) of the 300 sampled articles were correctly classified in MEDLINE as evaluative studies. The majority of the identified evaluative studies were published in medical education journals, confirming the integrity of medical education as a specialty. Findings concerning the study types published in medical education versus GIM journals are important for medical education researchers who seek to publish outside the field's specialty journals.

Frequency and content analysis of chronic fatigue syndrome in medical text books.

PubMed

Jason, Leonard A; Paavola, Erin; Porter, Nicole; Morello, Morgan L

2010-01-01

Text books are a cornerstone in the training of medical staff and students, and they are an important source of references and reviews for these professionals. The objective of this study was to determine both the quantity and quality of chronic fatigue syndrome (CFS) information included in medical texts. After reviewing 119 medical text books from various medical specialties, we found that 48 (40.3%) of the medical text books included information on CFS. However, among the 129 527 total pages within these medical text books, the CFS content was presented on only 116.3 (0.090%) pages. Other illnesses that are less prevalent, such as multiple sclerosis and Lyme disease, were more frequently represented in medical text books. These findings suggest that the topic ofCFS is underreported in published medical text books.

Optimal Embedding for Shape Indexing in Medical Image Databases

PubMed Central

Qian, Xiaoning; Tagare, Hemant D.; Fulbright, Robert K.; Long, Rodney; Antani, Sameer

2010-01-01

This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine x-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape-similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. PMID:20163981

Optimal embedding for shape indexing in medical image databases.

PubMed

Qian, Xiaoning; Tagare, Hemant D; Fulbright, Robert K; Long, Rodney; Antani, Sameer

2010-06-01

This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine X-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Language Functions and Medical Communication: The Human Body as Text

ERIC Educational Resources Information Center

Kantz, Deirdre; Marenzi, Ivana

2016-01-01

This article presents the findings of a field experiment in medical English with first-year medical students at the University of Pavia, Northern Italy. Working in groups of 8-10, the students were asked to produce a corpus of medical texts in English demonstrating how the human body is itself a meaningful text (Baldry and Thibault 2006: Ch. 1).…

Statistical text classifier to detect specific type of medical incidents.

PubMed

Wong, Zoie Shui-Yee; Akiyama, Masanori

2013-01-01

WHO Patient Safety has put focus to increase the coherence and expressiveness of patient safety classification with the foundation of International Classification for Patient Safety (ICPS). Text classification and statistical approaches has showed to be successful to identifysafety problems in the Aviation industryusing incident text information. It has been challenging to comprehend the taxonomy of medical incidents in a structured manner. Independent reporting mechanisms for patient safety incidents have been established in the UK, Canada, Australia, Japan, Hong Kong etc. This research demonstrates the potential to construct statistical text classifiers to detect specific type of medical incidents using incident text data. An illustrative example for classifying look-alike sound-alike (LASA) medication incidents using structured text from 227 advisories related to medication errors from Global Patient Safety Alerts (GPSA) is shown in this poster presentation. The classifier was built using logistic regression model. ROC curve and the AUC value indicated that this is a satisfactory good model.

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network.

PubMed

Tix, Nadine; Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

2015-11-11

The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM's semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively.

[On two antique medical texts].

PubMed

Rosa, Maria Carlota

2005-01-01

The two texts presented here--Regimento proueytoso contra ha pestenença [literally, "useful regime against pestilence"] and Modus curandi cum balsamo ["curing method using balm"]--represent the extent of Portugal's known medical library until circa 1530, produced in gothic letters by foreign printers: Germany's Valentim Fernandes, perhaps the era's most important printer, who worked in Lisbon between 1495 and 1518, and Germdo Galharde, a Frenchman who practiced his trade in Lisbon and Coimbra between 1519 and 1560. Modus curandi, which came to light in 1974 thanks to bibliophile José de Pina Martins, is anonymous. Johannes Jacobi is believed to be the author of Regimento proueytoso, which was translated into Latin (Regimen contra pestilentiam), French, and English. Both texts are presented here in facsimile and in modern Portuguese, while the first has also been reproduced in archaic Portuguese using modern typographical characters. This philological venture into sixteenth-century medicine is supplemented by a scholarly glossary which serves as a valuable tool in interpreting not only Regimento proueytoso but also other texts from the era. Two articles place these documents in historical perspective.

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network

PubMed Central

Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

2015-01-01

Background The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM’s semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. Objective The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. Methods In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. Results The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. Conclusions It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively. PMID:27731860

PASTE: patient-centered SMS text tagging in a medication management system.

PubMed

Stenner, Shane P; Johnson, Kevin B; Denny, Joshua C

2012-01-01

To evaluate the performance of a system that extracts medication information and administration-related actions from patient short message service (SMS) messages. Mobile technologies provide a platform for electronic patient-centered medication management. MyMediHealth (MMH) is a medication management system that includes a medication scheduler, a medication administration record, and a reminder engine that sends text messages to cell phones. The object of this work was to extend MMH to allow two-way interaction using mobile phone-based SMS technology. Unprompted text-message communication with patients using natural language could engage patients in their healthcare, but presents unique natural language processing challenges. The authors developed a new functional component of MMH, the Patient-centered Automated SMS Tagging Engine (PASTE). The PASTE web service uses natural language processing methods, custom lexicons, and existing knowledge sources to extract and tag medication information from patient text messages. A pilot evaluation of PASTE was completed using 130 medication messages anonymously submitted by 16 volunteers via a website. System output was compared with manually tagged messages. Verified medication names, medication terms, and action terms reached high F-measures of 91.3%, 94.7%, and 90.4%, respectively. The overall medication name F-measure was 79.8%, and the medication action term F-measure was 90%. Other studies have demonstrated systems that successfully extract medication information from clinical documents using semantic tagging, regular expression-based approaches, or a combination of both approaches. This evaluation demonstrates the feasibility of extracting medication information from patient-generated medication messages.

PASTE: patient-centered SMS text tagging in a medication management system

PubMed Central

Johnson, Kevin B; Denny, Joshua C

2011-01-01

Objective To evaluate the performance of a system that extracts medication information and administration-related actions from patient short message service (SMS) messages. Design Mobile technologies provide a platform for electronic patient-centered medication management. MyMediHealth (MMH) is a medication management system that includes a medication scheduler, a medication administration record, and a reminder engine that sends text messages to cell phones. The object of this work was to extend MMH to allow two-way interaction using mobile phone-based SMS technology. Unprompted text-message communication with patients using natural language could engage patients in their healthcare, but presents unique natural language processing challenges. The authors developed a new functional component of MMH, the Patient-centered Automated SMS Tagging Engine (PASTE). The PASTE web service uses natural language processing methods, custom lexicons, and existing knowledge sources to extract and tag medication information from patient text messages. Measurements A pilot evaluation of PASTE was completed using 130 medication messages anonymously submitted by 16 volunteers via a website. System output was compared with manually tagged messages. Results Verified medication names, medication terms, and action terms reached high F-measures of 91.3%, 94.7%, and 90.4%, respectively. The overall medication name F-measure was 79.8%, and the medication action term F-measure was 90%. Conclusion Other studies have demonstrated systems that successfully extract medication information from clinical documents using semantic tagging, regular expression-based approaches, or a combination of both approaches. This evaluation demonstrates the feasibility of extracting medication information from patient-generated medication messages. PMID:21984605

The great contribution: Index Medicus, Index-Catalogue, and IndexCat

PubMed Central

Greenberg, Stephen J.; Gallagher, Patricia E.

2009-01-01

Objective: The systematic indexing of medical literature by the Library of the Surgeon-General's Office (now the National Library of Medicine) has been called “America's greatest contribution to medical knowledge.” In the 1870s, the library launched two indexes: the Index Medicus and the Index-Catalogue of the Library of the Surgeon-General's Office. Index Medicus is better remembered today as the forerunner of MEDLINE, but Index Medicus began as the junior partner of what the library saw as its major publication, the Index-Catalogue. However, the Index-Catalogue had been largely overlooked by many medical librarians until 2004, when the National Library of Medicine released IndexCat, the online version of Index-Catalogue. Access to this huge amount of material raised new questions: What was the coverage of the Index-Catalogue? How did it compare and overlap with the Index Medicus? Method: Over 1,000 randomly generated Index Medicus citations were cross-referenced in IndexCat. Results: Inclusion, form, content, authority control, and subject headings were evaluated, revealing that the relationship between the two publications was neither simple nor static through time. In addition, the authors found interesting anomalies that shed light on how medical literature was selected and indexed in “America's greatest contribution to medical knowledge.” PMID:19404501

Using Bitmap Indexing Technology for Combined Numerical and TextQueries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stockinger, Kurt; Cieslewicz, John; Wu, Kesheng

2006-10-16

In this paper, we describe a strategy of using compressedbitmap indices to speed up queries on both numerical data and textdocuments. By using an efficient compression algorithm, these compressedbitmap indices are compact even for indices with millions of distinctterms. Moreover, bitmap indices can be used very efficiently to answerBoolean queries over text documents involving multiple query terms.Existing inverted indices for text searches are usually inefficient forcorpora with a very large number of terms as well as for queriesinvolving a large number of hits. We demonstrate that our compressedbitmap index technology overcomes both of those short-comings. In aperformance comparison against amore » commonly used database system, ourindices answer queries 30 times faster on average. To provide full SQLsupport, we integrated our indexing software, called FastBit, withMonetDB. The integrated system MonetDB/FastBit provides not onlyefficient searches on a single table as FastBit does, but also answersjoin queries efficiently. Furthermore, MonetDB/FastBit also provides avery efficient retrieval mechanism of result records.« less

Visualization of semantic indexing similarity over MeSH.

PubMed

Du, Haixia; Yoo, Terry S

2007-10-11

We present an interactive visualization system for the evaluation of indexing results of the MEDLINE data-base over the Medical Subject Headings (MeSH) structure in a graphical radial-tree layout. It displays indexing similarity measurements with 2D color coding and a 3D height field permitting the evaluation of the automatic Medical Text Indexer (MTI), compared with human indexers.

Index of Submarine Medical Officer’s Qualification Theses 1944-1974

DTIC Science & Technology

1976-04-01

Preface The theses listed in this index are available only from the Naval Undersea Medical Institute (NUMI). They have not been . duplicated for...Officer in Charge Naval Undersea Medical Institute Box 159 Naval Submarine Base New London Groton, Connecticut 06340 ii ABSTRACT A candidate for...submitted to the Naval Undersea Medical Institute in the form of a thesis. Several interesting and worthwhile projects have been completed under this

Frequency and Content Analysis of CFS in Medical Text Books

PubMed Central

Jason, Leonard A.; Paavola, Erin; Porter, Nicole; Morello, Morgan L.

2013-01-01

Textbooks are a cornerstone in the training of medical staff and students, and they are an important source of references and reviews for these professionals. The objective of this study was to determine both the quantity and quality of chronic fatigue syndrome (CFS) information included in medical texts. After reviewing 119 medical textbooks from various medical specialties, we found that 48 (40.3%) of the medical textbooks included information on CFS. However, among the 129,527 total pages within these medical textbooks, the CFS content was presented on only 116.3 (.090%) pages. Other illnesses that are less prevalent, such as Multiple Sclerosis and Lyme disease, were more frequently represented in medical textbooks. These findings suggest that the topic of CFS is under-reported in published medical textbooks. PMID:21128580

Extracting Characteristics of the Study Subjects from Full-Text Articles

PubMed Central

Demner-Fushman, Dina; Mork, James G

2015-01-01

Characteristics of the subjects of biomedical research are important in determining if a publication describing the research is relevant to a search. To facilitate finding relevant publications, MEDLINE citations provide Medical Subject Headings that describe the subjects’ characteristics, such as their species, gender, and age. We seek to improve the recommendation of these headings by the Medical Text Indexer (MTI) that supports manual indexing of MEDLINE. To that end, we explore the potential of the full text of the publications. Using simple recall-oriented rule-based methods we determined that adding sentences extracted from the methods sections and captions to the abstracts prior to MTI processing significantly improved recall and F1 score with only a slight drop in precision. Improvements were also achieved in directly assigning several headings extracted from the full text. These results indicate the need for further development of automated methods capable of leveraging the full text for indexing. PMID:26958181

Medical care price indexes: theory, construction & empirical analysis of the US series 1927-1990.

PubMed

Getzen, T E

1992-01-01

The historical development of price indexes as wage adjustment mechanisms is reviewed, as is the theory of aggregation and methods for dealing with quality and technological change. The construction of the U.S. Bureau of Labor Statistics (BLS) Medical Care Price Index (MCPI) is detailed. ARIMA analysis of the MCPI for the period 1927-1990 indicates that; (i) the MCPI is largely a damped and delayed function of the CPI, with an average lag of 8 months; (ii) medical care prices rose 2-4 percent faster than the all-items CPI since 1950, but not for 1927-1950; (iii) health expenditures are affected primarily by the general CPI, with little independent effect of specifically medical prices. The MCPI is a reliable measure of changes in consumer prices with strong construct validity. However, it was not designed for use as a deflator of medical expenditures, and is misleading when erroneously employed in that unintended role. The price/quantity duality and linear expenditure function which form the basis of Laspeyres price indexes are not applicable to nonconcatenable goods such as insurance or medical care. In these complex transactions, quality dominates quantity, fixed prices are replaced by reimbursement and professional judgement, and the assumption of additive separability required to use the price index as a deflator of health expenditures is not valid.

Reflective random indexing for semi-automatic indexing of the biomedical literature.

PubMed

Vasuki, Vidya; Cohen, Trevor

2010-10-01

The rapid growth of biomedical literature is evident in the increasing size of the MEDLINE research database. Medical Subject Headings (MeSH), a controlled set of keywords, are used to index all the citations contained in the database to facilitate search and retrieval. This volume of citations calls for efficient tools to assist indexers at the US National Library of Medicine (NLM). Currently, the Medical Text Indexer (MTI) system provides assistance by recommending MeSH terms based on the title and abstract of an article using a combination of distributional and vocabulary-based methods. In this paper, we evaluate a novel approach toward indexer assistance by using nearest neighbor classification in combination with Reflective Random Indexing (RRI), a scalable alternative to the established methods of distributional semantics. On a test set provided by the NLM, our approach significantly outperforms the MTI system, suggesting that the RRI approach would make a useful addition to the current methodologies.

Using Medical Text Extraction, Reasoning and Mapping System (MTERMS) to Process Medication Information in Outpatient Clinical Notes

PubMed Central

Zhou, Li; Plasek, Joseph M; Mahoney, Lisa M; Karipineni, Neelima; Chang, Frank; Yan, Xuemin; Chang, Fenny; Dimaggio, Dana; Goldman, Debora S.; Rocha, Roberto A.

2011-01-01

Clinical information is often coded using different terminologies, and therefore is not interoperable. Our goal is to develop a general natural language processing (NLP) system, called Medical Text Extraction, Reasoning and Mapping System (MTERMS), which encodes clinical text using different terminologies and simultaneously establishes dynamic mappings between them. MTERMS applies a modular, pipeline approach flowing from a preprocessor, semantic tagger, terminology mapper, context analyzer, and parser to structure inputted clinical notes. Evaluators manually reviewed 30 free-text and 10 structured outpatient clinical notes compared to MTERMS output. MTERMS achieved an overall F-measure of 90.6 and 94.0 for free-text and structured notes respectively for medication and temporal information. The local medication terminology had 83.0% coverage compared to RxNorm’s 98.0% coverage for free-text notes. 61.6% of mappings between the terminologies are exact match. Capture of duration was significantly improved (91.7% vs. 52.5%) from systems in the third i2b2 challenge. PMID:22195230

Construction of an evaluation index system for determining the academic impact of military medical scholars.

PubMed

Li, Xuan; Hao, J Y

2018-01-13

Academic papers are an essential manner for describing new ideas and consolidating existing concepts in the field of military medicine. The academic impact of military medical publications reflects the extent and depth of recognition, acceptance and utilisation of the concepts transmitted in these publications. The aim of this research was to construct an evaluation index system suitable for evaluating the academic influence of scholars in the field of military medicine. Using the Delphi consensus methodology, 30 experts from the field of military medicine, military medical information and library and information science were asked during three rounds of questioning to score the feasibility and importance of indicators that could be used to determine academic impact. An analytic hierarchy process method was used to calculate the relative weighting of each indicator in determining the final level of academic impact. Eight evaluation indicators were agreed on to potentially determine academic impact. These comprised: 'Web of Science documents', 'Citation impact', 'h-index', 'Percentage of international collaborations', 'Percentage of the top 10% of the cited frequency', 'Category normalised citation impact', 'Percentage of documents cited' and 'The number of F1000 Recommended papers'. The evaluation index system determined from this study combines the advantages of both qualitative and quantitative recognised evaluation indicators, which are subsequently weighted according to their importance in the field of military medicine. It is hoped that this framework will provide a manner in the future for comparing the potential academic impact of military medical scholars. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Timing of Gestures: Gestures Anticipating or Simultaneous with Speech as Indexes of Text Comprehension in Children and Adults

ERIC Educational Resources Information Center

Ianì, Francesco; Cutica, Ilaria; Bucciarelli, Monica

2017-01-01

The deep comprehension of a text is tantamount to the construction of an articulated mental model of that text. The number of correct recollections is an index of a learner's mental model of a text. We assume that another index of comprehension is the timing of the gestures produced during text recall; gestures are simultaneous with speech when…

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

NASA Indexing Benchmarks: Evaluating Text Search Engines

NASA Technical Reports Server (NTRS)

Esler, Sandra L.; Nelson, Michael L.

1997-01-01

The current proliferation of on-line information resources underscores the requirement for the ability to index collections of information and search and retrieve them in a convenient manner. This study develops criteria for analytically comparing the index and search engines and presents results for a number of freely available search engines. A product of this research is a toolkit capable of automatically indexing, searching, and extracting performance statistics from each of the focused search engines. This toolkit is highly configurable and has the ability to run these benchmark tests against other engines as well. Results demonstrate that the tested search engines can be grouped into two levels. Level one engines are efficient on small to medium sized data collections, but show weaknesses when used for collections 100MB or larger. Level two search engines are recommended for data collections up to and beyond 100MB.

MeSH indexing based on automatically generated summaries.

PubMed

Jimeno-Yepes, Antonio J; Plaza, Laura; Mork, James G; Aronson, Alan R; Díaz, Alberto

2013-06-26

MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most

MeSH indexing based on automatically generated summaries

PubMed Central

2013-01-01

Background MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. Results We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Conclusions Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can

A system for de-identifying medical message board text.

PubMed

Benton, Adrian; Hill, Shawndra; Ungar, Lyle; Chung, Annie; Leonard, Charles; Freeman, Cristin; Holmes, John H

2011-06-09

There are millions of public posts to medical message boards by users seeking support and information on a wide range of medical conditions. It has been shown that these posts can be used to gain a greater understanding of patients' experiences and concerns. As investigators continue to explore large corpora of medical discussion board data for research purposes, protecting the privacy of the members of these online communities becomes an important challenge that needs to be met. Extant entity recognition methods used for more structured text are not sufficient because message posts present additional challenges: the posts contain many typographical errors, larger variety of possible names, terms and abbreviations specific to Internet posts or a particular message board, and mentions of the authors' personal lives. The main contribution of this paper is a system to de-identify the authors of message board posts automatically, taking into account the aforementioned challenges. We demonstrate our system on two different message board corpora, one on breast cancer and another on arthritis. We show that our approach significantly outperforms other publicly available named entity recognition and de-identification systems, which have been tuned for more structured text like operative reports, pathology reports, discharge summaries, or newswire.

A model for indexing medical documents combining statistical and symbolic knowledge.

PubMed

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-10-11

To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.

A Model for Indexing Medical Documents Combining Statistical and Symbolic Knowledge.

PubMed Central

Avillach, Paul; Joubert, Michel; Fieschi, Marius

2007-01-01

OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the model’s implementation performances as a result of using semantic relationships is encouraging. PMID:18693792

Terminology extraction from medical texts in Polish

PubMed Central

2014-01-01

Background Hospital documents contain free text describing the most important facts relating to patients and their illnesses. These documents are written in specific language containing medical terminology related to hospital treatment. Their automatic processing can help in verifying the consistency of hospital documentation and obtaining statistical data. To perform this task we need information on the phrases we are looking for. At the moment, clinical Polish resources are sparse. The existing terminologies, such as Polish Medical Subject Headings (MeSH), do not provide sufficient coverage for clinical tasks. It would be helpful therefore if it were possible to automatically prepare, on the basis of a data sample, an initial set of terms which, after manual verification, could be used for the purpose of information extraction. Results Using a combination of linguistic and statistical methods for processing over 1200 children hospital discharge records, we obtained a list of single and multiword terms used in hospital discharge documents written in Polish. The phrases are ordered according to their presumed importance in domain texts measured by the frequency of use of a phrase and the variety of its contexts. The evaluation showed that the automatically identified phrases cover about 84% of terms in domain texts. At the top of the ranked list, only 4% out of 400 terms were incorrect while out of the final 200, 20% of expressions were either not domain related or syntactically incorrect. We also observed that 70% of the obtained terms are not included in the Polish MeSH. Conclusions Automatic terminology extraction can give results which are of a quality high enough to be taken as a starting point for building domain related terminological dictionaries or ontologies. This approach can be useful for preparing terminological resources for very specific subdomains for which no relevant terminologies already exist. The evaluation performed showed that none of the

Terminology extraction from medical texts in Polish.

PubMed

Marciniak, Małgorzata; Mykowiecka, Agnieszka

2014-01-01

Hospital documents contain free text describing the most important facts relating to patients and their illnesses. These documents are written in specific language containing medical terminology related to hospital treatment. Their automatic processing can help in verifying the consistency of hospital documentation and obtaining statistical data. To perform this task we need information on the phrases we are looking for. At the moment, clinical Polish resources are sparse. The existing terminologies, such as Polish Medical Subject Headings (MeSH), do not provide sufficient coverage for clinical tasks. It would be helpful therefore if it were possible to automatically prepare, on the basis of a data sample, an initial set of terms which, after manual verification, could be used for the purpose of information extraction. Using a combination of linguistic and statistical methods for processing over 1200 children hospital discharge records, we obtained a list of single and multiword terms used in hospital discharge documents written in Polish. The phrases are ordered according to their presumed importance in domain texts measured by the frequency of use of a phrase and the variety of its contexts. The evaluation showed that the automatically identified phrases cover about 84% of terms in domain texts. At the top of the ranked list, only 4% out of 400 terms were incorrect while out of the final 200, 20% of expressions were either not domain related or syntactically incorrect. We also observed that 70% of the obtained terms are not included in the Polish MeSH. Automatic terminology extraction can give results which are of a quality high enough to be taken as a starting point for building domain related terminological dictionaries or ontologies. This approach can be useful for preparing terminological resources for very specific subdomains for which no relevant terminologies already exist. The evaluation performed showed that none of the tested ranking procedures were

Automatic indexing of compound words based on mutual information for Korean text retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan Koo Kim; Yoo Kun Cho

In this paper, we present an automatic indexing technique for compound words suitable to an aggulutinative language, specifically Korean. Firstly, we present the construction conditions to compose compound words as indexing terms. Also we present the decomposition rules applicable to consecutive nouns to extract all contents of text. Finally we propose a measure to estimate the usefulness of a term, mutual information, to calculate the degree of word association of compound words, based on the information theoretic notion. By applying this method, our system has raised the precision rate of compound words from 72% to 87%.

Indexing the medical open access literature for textual and content-based visual retrieval.

PubMed

Eggel, Ivan; Müller, Henning

2010-01-01

Over the past few years an increasing amount of scientific journals have been created in an open access format. Particularly in the medical field the number of openly accessible journals is enormous making a wide body of knowledge available for analysis and retrieval. Part of the trend towards open access publications can be linked to funding bodies such as the NIH¹ (National Institutes of Health) and the Swiss National Science Foundation (SNF²) requiring funded projects to make all articles of funded research available publicly. This article describes an approach to make part of the knowledge of open access journals available for retrieval including the textual information but also the images contained in the articles. For this goal all articles of 24 journals related to medical informatics and medical imaging were crawled from the web pages of BioMed Central. Text and images of the PDF (Portable Document Format) files were indexed separately and a web-based retrieval interface allows for searching via keyword queries or by visual similarity queries. Starting point for a visual similarity query can be an image on the local hard disk that is uploaded or any image found via the textual search. Search for similar documents is also possible.

Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis.

PubMed

Thakkar, Jay; Kurup, Rahul; Laba, Tracey-Lea; Santo, Karla; Thiagalingam, Aravinda; Rodgers, Anthony; Woodward, Mark; Redfern, Julie; Chow, Clara K

2016-03-01

Adherence to long-term therapies in chronic disease is poor. Traditional interventions to improve adherence are complex and not widely effective. Mobile telephone text messaging may be a scalable means to support medication adherence. To conduct a meta-analysis of randomized clinical trials to assess the effect of mobile telephone text messaging on medication adherence in chronic disease. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL (from database inception to January 15, 2015), as well as reference lists of the articles identified. The data were analyzed in March 2015. Randomized clinical trials evaluating a mobile telephone text message intervention to promote medication adherence in adults with chronic disease. Two authors independently extracted information on study characteristics, text message characteristics, and outcome measures as per the predefined protocol. Odds ratios and pooled data were calculated using random-effects models. Risk of bias and study quality were assessed as per Cochrane guidelines. Disagreement was resolved by consensus. Sixteen randomized clinical trials were included, with 5 of 16 using personalization, 8 of 16 using 2-way communication, and 8 of 16 using a daily text message frequency. The median intervention duration was 12 weeks, and self-report was the most commonly used method to assess medication adherence. In the pooled analysis of 2742 patients (median age, 39 years and 50.3% [1380 of 2742] female), text messaging significantly improved medication adherence (odds ratio, 2.11; 95% CI, 1.52-2.93; P < .001). The effect was not sensitive to study characteristics (intervention duration or type of disease) or text message characteristics (personalization, 2-way communication, or daily text message frequency). In a sensitivity analysis, our findings remained robust to change in inclusion criteria based on study quality (odds ratio, 1.67; 95% CI, 1.21-2.29; P = .002). There was moderate

Automatic inference of indexing rules for MEDLINE.

PubMed

Névéol, Aurélie; Shooshan, Sonya E; Claveau, Vincent

2008-11-19

Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE. In this paper, we describe the use and the customization of Inductive Logic Programming (ILP) to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers. Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI), a system producing automatic indexing recommendations for MEDLINE. We expect the sets of ILP rules obtained in this experiment to be integrated into MTI.

One-way versus two-way text messaging on improving medication adherence: meta-analysis of randomized trials.

PubMed

Wald, David S; Butt, Shahena; Bestwick, Jonathan P

2015-10-01

Mobile telephone text messaging is a simple potential solution to the failure to take medications as directed. There is uncertainty over the effectiveness of 1-way text messaging (sending text message reminders only) compared with 2-way text messaging (sending reminders and receiving replies confirming whether medication has been taken) as a means of improving medication adherence. A meta-analysis of 8 randomized trials (1994 patients) that tested the effectiveness of text messaging on medication adherence was performed. The trials were divided into 2 groups: trials using 1-way text messaging versus no text messaging and trials using 2-way text messaging versus no text messaging. The summary estimates of the effect of the 2 methods of text messaging (1-way or 2-way) were compared. The summary relative risk estimate was 1.04 (95% confidence interval, 0.97-1.11) for 1-way text messaging and 1.23 (95% confidence interval, 1.13-1.35) for 2-way text messaging. The difference in effect between the 2 methods was statistically significant (P = .007). Two-way text messaging is associated with substantially improved medication adherence compared with 1-way text messaging. This has important implications in the provision of mobile-based messaging in the management of patients taking medication for the prevention of chronic disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation of emergency medical text processor, a system for cleaning chief complaint text data.

PubMed

Travers, Debbie A; Haas, Stephanie W

2004-11-01

Emergency Medical Text Processor (EMT-P) version 1, a natural language processing system that cleans emergency department text (e.g., chst pn, chest pai), was developed to maximize extraction of standard terms (e.g., chest pain). The authors compared the number of standard terms extracted from raw chief complaint (CC) data with that for CC data cleaned with EMT-P and evaluated the accuracy of EMT-P. This cross-sectional observation study included CC text entries for all emergency department visits to three tertiary care centers in 2001. Terms were extracted from CC entries before and after cleaning with EMT-P. Descriptive statistics included number and percentage of all entries (tokens) and all unique entries (types) that matched a standard term from the Unified Medical Language System (UMLS). An expert panel rated the accuracy of the CC-UMLS term matches; inter-rater reliability was measured with kappa. The authors collected 203,509 CC entry tokens, of which 63,946 were unique entry types. For the raw data, 89,337 tokens (44%) and 5,081 types (8%) matched a standard term. After EMT-P cleaning, 168,050 tokens (83%) and 44,430 types (69%) matched a standard term. The expert panel reached consensus on 201 of the 222 CC-UMLS term matches reviewed (kappa=0.69-0.72). Ninety-six percent of the 201 matches were rated equivalent or related. Thirty-eight percent of the nonmatches were found to match UMLS concepts. EMT-P version 1 is relatively accurate, and cleaning with EMT-P improved the CC-UMLS term match rate over raw data. The authors identified areas for improvement in future EMT-P versions and issues to be resolved in developing a standard CC terminology.

Automatic inference of indexing rules for MEDLINE

PubMed Central

Névéol, Aurélie; Shooshan, Sonya E; Claveau, Vincent

2008-01-01

Background: Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to describe the subject matter of articles. The need for automatic tools to assist MEDLINE indexers in this task is growing with the increasing number of publications being added to MEDLINE. Methods: In this paper, we describe the use and the customization of Inductive Logic Programming (ILP) to infer indexing rules that may be used to produce automatic indexing recommendations for MEDLINE indexers. Results: Our results show that this original ILP-based approach outperforms manual rules when they exist. In addition, the use of ILP rules also improves the overall performance of the Medical Text Indexer (MTI), a system producing automatic indexing recommendations for MEDLINE. Conclusion: We expect the sets of ILP rules obtained in this experiment to be integrated into MTI. PMID:19025687

Texting atopic dermatitis patients to optimize learning and eczema area and severity index scores: A pilot randomized control trial.

PubMed

Singer, Hannah M; Levin, Laura E; Morel, Kimberly D; Garzon, Maria C; Stockwell, Melissa S; Lauren, Christine T

2018-05-02

Atopic dermatitis is a common, chronic, debilitating disease. Poor adherence to treatment is the most important preventable contributor to adverse outcomes. Thus, improving adherence can improve patient outcomes. Text message reminders with embedded condition-specific information have been shown to improve pediatric immunization adherence but have not been assessed in atopic dermatitis. The objective was to assess the effect of daily text messages on Eczema Area Severity Index scores and caregiver knowledge of atopic dermatitis. In this pilot randomized controlled trial, caregivers of children with atopic dermatitis enrolled during their initial appointment with a pediatric dermatologist and randomized 1:1 to standard care or daily text messages with patient education material and treatment reminders. Participants completed a multiple-choice atopic dermatitis knowledge quiz at initial and follow-up visits, and Eczema Area Severity Index scores were assessed. Forty-two patients enrolled, and 30 completed the study: 16 standard care group, 14 text message group. There was no significant difference in Eczema Area Severity Index score between the standard care and text message groups at follow-up, with mean decreases in Eczema Area Severity Index score of 53% and 58%, respectively. Mean score on follow-up atopic dermatitis knowledge quiz was significantly higher in the text message group (84% correct) than in the standard care group (75% correct) (P = .04). This pilot study did not demonstrate a difference in Eczema Area Severity Index scores with text message reminders. The significantly higher follow-up atopic dermatitis quiz score in the text message group indicates that participants read and retained information from text messages. Limitations include small sample size and short duration of follow-up. © 2018 Wiley Periodicals, Inc.

Economic Evaluation of Text-Messaging and Smartphone-Based Interventions to Improve Medication Adherence in Adolescents with Chronic Health Conditions: A Systematic Review.

PubMed

Badawy, Sherif M; Kuhns, Lisa M

2016-10-25

The rate of chronic health conditions (CHCs) in children and adolescents has doubled in the past 20 years, with increased health care costs. Technology-based interventions have demonstrated efficacy to improving medication adherence. However, data to support the cost effectiveness of these interventions are lacking. The objective of this study is to conduct an economic evaluation of text-messaging and smartphone-based interventions that focus on improving medication adherence in adolescents with CHCs. Searches included PubMed MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Web of Science, and Inspec. Eligibility criteria included age (12-24 years old), original articles, outcomes for medication adherence, and economic outcomes. Our search identified 1118 unique articles that were independently screened. A total of 156 articles met inclusion criteria and were then examined independently with full-text review. A total of 15 articles met most criteria but lacked economic outcomes such as cost effectiveness or cost-utility data. No articles met all predefined criteria to be included for final review. Only 4 articles (text messaging [n=3], electronic directly observed therapy [n=1]) described interventions with possible future cost-saving but no formal economic evaluation. The evidence to support the cost effectiveness of text-messaging and smartphone-based interventions in improving medication adherence in adolescents with CHCs is insufficient. This lack of research highlights the need for comprehensive economic evaluation of such interventions to better understand their role in cost-savings while improving medication adherence and health outcomes. Economic evaluation of technology-based interventions can contribute to more evidence-based assessment of the scalability, sustainability, and benefits of broader investment of such technology tools in adolescents with CHCs.

Data Processing and Text Mining Technologies on Electronic Medical Records: A Review

PubMed Central

Sun, Wencheng; Li, Yangyang; Liu, Fang; Fang, Shengqun; Wang, Guoyan

2018-01-01

Currently, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed, and treatment results. EMR has been recognized as a valuable resource for large-scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy, and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation, and data reduction. For semistructured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (named-entity recognition) and RE (relation extraction). This paper focuses on the process of EMR processing and emphatically analyzes the key techniques. In addition, we make an in-depth study on the applications developed based on text mining together with the open challenges and research issues for future work. PMID:29849998

Strategies for searching medical natural language text. Distribution of words in the anatomic diagnoses of 7000 autopsy subjects.

PubMed Central

Moore, G. W.; Hutchins, G. M.; Miller, R. E.

1984-01-01

Computerized indexing and retrieval of medical records is increasingly important; but the use of natural language versus coded languages (SNOP, SNOMED) for this purpose remains controversial. In an effort to develop search strategies for natural language text, the authors examined the anatomic diagnosis reports by computer for 7000 consecutive autopsy subjects spanning a 13-year period at The Johns Hopkins Hospital. There were 923,657 words, 11,642 of them distinct. The authors observed an average of 1052 keystrokes, 28 lines, and 131 words per autopsy report, with an average 4.6 words per line and 7.0 letters per word. The entire text file represented 921 hours of secretarial effort. Words ranged in frequency from 33,959 occurrences of "and" to one occurrence for each of 3398 different words. Searches for rare diseases with unique names or for representative examples of common diseases were most readily performed with the use of computer-printed key word in context (KWIC) books. For uncommon diseases designated by commonly used terms (such as "cystic fibrosis"), needs were best served by a computerized search for logical combinations of key words. In an unbalanced word distribution, each conjunction (logical and) search should be performed in ascending order of word frequency; but each alternation (logical inclusive or) search should be performed in descending order of word frequency. Natural language text searches will assume a larger role in medical records analysis as the labor-intensive procedure of translation into a coded language becomes more costly, compared with the computer-intensive procedure of text searching. PMID:6546837

Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues

NASA Astrophysics Data System (ADS)

Adams, W. H.; Iyengar, Giridharan; Lin, Ching-Yung; Naphade, Milind Ramesh; Neti, Chalapathy; Nock, Harriet J.; Smith, John R.

2003-12-01

We present a learning-based approach to the semantic indexing of multimedia content using cues derived from audio, visual, and text features. We approach the problem by developing a set of statistical models for a predefined lexicon. Novel concepts are then mapped in terms of the concepts in the lexicon. To achieve robust detection of concepts, we exploit features from multiple modalities, namely, audio, video, and text. Concept representations are modeled using Gaussian mixture models (GMM), hidden Markov models (HMM), and support vector machines (SVM). Models such as Bayesian networks and SVMs are used in a late-fusion approach to model concepts that are not explicitly modeled in terms of features. Our experiments indicate promise in the proposed classification and fusion methodologies: our proposed fusion scheme achieves more than 10% relative improvement over the best unimodal concept detector.

Masters theses from a university medical college: publication in indexed scientific journals.

PubMed

Dhaliwal, Upreet; Singh, Navjeevan; Bhatia, Arati

2010-01-01

The thesis is an integral part of postgraduate medical education in India. Publication of the results of the thesis in an indexed journal is desirable; it validates the research and makes results available to researchers worldwide. To determine publication rates in indexed journals, of works derived from theses, and factors affecting publication. Postgraduate theses submitted over a five-year period (2001-05) in a university medical college were analyzed in a retrospective, observational study. Data retrieved included name and gender of postgraduate student, names, department and hierarchy of supervisor and co-supervisor(s), year submitted, study design, sample size, and statistically significant difference between groups. To determine subsequent publication in an indexed journal, Medline search was performed up to December 2007. Chi square test was used to compare publication rates based on categorical variables; Student's t-test was used to compare differences based on continuous variables. One hundred and sixty theses were retrieved, forty-eight (30%) were published. Papers were published 8-74 (33.7+/-17.33) months after thesis submission; the postgraduate student was first author in papers from 26 (54%) of the published theses. Gender of the student, department of origin, year of thesis submission, hierarchy of the supervisor, number and department of co-supervisors, and thesis characteristics did not influence publication rates. Rate of publication in indexed journals, of papers derived from postgraduate theses is 30%. In this study we were unable to identify factors that promote publication.

A comparative study of the origin, structure, and indexing language of the Persian and English keywords of articles indexed in the IranMedex database and their compliance with the Persian medical thesaurus and Medical Subject Headings.

PubMed

Parsaei-Mohammadi, Parastoo; Ghasemi, Ali Hossein; Hassanzadeh-Beheshtabad, Raziyeh

2017-01-01

In the present era, thesauri as tools in indexing play an effective role in integrating retrieval preventing fragmentation as well as a multiplicity of terminologies and also in providing information content of documents. This study aimed to investigate the keywords of articles indexed in IranMedex in terms of origin, structure and indexing situation and their Compliance with the Persian Medical Thesaurus and Medical Subject Headings (MeSH). This study is an applied research, and a survey has been conducted. Statistical population includes 32,850 Persian articles which are indexed in the IranMedex during the years 1385-1391. 379 cases were selected as sample of the study. Data collection was done using a checklist. In analyzing the findings, the SPSS Software were used. Although there was no significant difference in terms of indexing origin between the proportion of different types of the Persian and English keywords of articles indexed in the IranMedex, the compliance rates of the Persian and English keywords with the Persian medical thesaurus and MeSH were different in different years. In the meantime, the structure of keywords is leaning more towards phrase structure, and a single word structure and the majority of keywords are selected from the titles and abstracts. The authors' familiarity with the thesauri and controlled tools causes homogeneity in assigning keywords and also provides more precise, faster, and easier retrieval of the keywords. It's suggested that a mixture of natural and control languages to be used in this database in order to reach more comprehensive results.

Mining free-text medical records for companion animal enteric syndrome surveillance.

PubMed

Anholt, R M; Berezowski, J; Jamal, I; Ribble, C; Stephen, C

2014-03-01

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals. Copyright © 2014 Elsevier B.V. All rights reserved.

E2FM: an encrypted and compressed full-text index for collections of genomic sequences.

PubMed

Montecuollo, Ferdinando; Schmid, Giovannni; Tagliaferri, Roberto

2017-09-15

Next Generation Sequencing (NGS) platforms and, more generally, high-throughput technologies are giving rise to an exponential growth in the size of nucleotide sequence databases. Moreover, many emerging applications of nucleotide datasets-as those related to personalized medicine-require the compliance with regulations about the storage and processing of sensitive data. We have designed and carefully engineered E 2 FM -index, a new full-text index in minute space which was optimized for compressing and encrypting nucleotide sequence collections in FASTA format and for performing fast pattern-search queries. E 2 FM -index allows to build self-indexes which occupy till to 1/20 of the storage required by the input FASTA file, thus permitting to save about 95% of storage when indexing collections of highly similar sequences; moreover, it can exactly search the built indexes for patterns in times ranging from few milliseconds to a few hundreds milliseconds, depending on pattern length. Source code is available at https://github.com/montecuollo/E2FM . ferdinando.montecuollo@unicampania.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Deprivation index and dependency ratio are key determinants of emergency medical admission rates.

PubMed

Conway, Richard; Byrne, Declan; O'Riordan, Deirdre; Cournane, Seán; Coveney, Seamus; Silke, Bernard

2015-11-01

Patients from deprived backgrounds have a higher in-patient mortality following an emergency medical admission; there has been debate as to the extent to which deprivation and population structure influences hospital admission rate. All emergency medical admissions to an Irish hospital over a 12-year period (2002-2013) categorized by quintile of Deprivation Index and Dependency Ratio (proportion of population <15 or ≥ 65 years) from small area population statistics (SAPS), were evaluated against hospital admission rates. Univariate and multivariable risk estimates (Odds Ratios (OR) or Incidence Rate Ratios (IRR)) were calculated, using logistic or zero truncated Poisson regression as appropriate. 66,861 admissions in 36,214 patients occured during the study period. The Deprivation Index quintile independently predicted the admission rate/1000 population, Q1 9.4 (95%CI 9.2 to 9.7), Q2 16.8 (95%CI 16.6 to 17.0), Q3 33.8 (95%CI 33.5 to 34.1), Q4 29.6 (95%CI 29.3 to 29.8) and Q5 45.4 (95%CI 44.5 to 46.2). Similarly the population Dependency Ratio was an independent predictor of the admission rate with adjusted predicted rates of Q1 20.8 (95%CI 20.5 to 21.1), Q2 19.2 (95%CI 19.0 to 19.4), Q3 27.6 (95%CI 27.3 to 27.9), Q4 43.9 (95%CI 43.5 to 44.4) and Q5 34.4 (95%CI 34.1 to 34.7). A high concurrent Deprivation Index and Dependency Ratio were associated with very high admission rates. Deprivation Index and population Dependency Ratio are key determinants of the rate of emergency medical admissions. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Masters theses from a university medical college: Publication in indexed scientific journals

PubMed Central

Dhaliwal, Upreet; Singh, Navjeevan; Bhatia, Arati

2010-01-01

Background: The thesis is an integral part of postgraduate medical education in India. Publication of the results of the thesis in an indexed journal is desirable; it validates the research and makes results available to researchers worldwide. Aims: To determine publication rates in indexed journals, of works derived from theses, and factors affecting publication. Settings and Design: Postgraduate theses submitted over a five-year period (2001-05) in a university medical college were analyzed in a retrospective, observational study. Materials and Methods: Data retrieved included name and gender of postgraduate student, names, department and hierarchy of supervisor and co-supervisor(s), year submitted, study design, sample size, and statistically significant difference between groups. To determine subsequent publication in an indexed journal, Medline search was performed up to December 2007. Statistical Analysis: Chi square test was used to compare publication rates based on categorical variables; Student's t-test was used to compare differences based on continuous variables. Results: One hundred and sixty theses were retrieved, forty-eight (30%) were published. Papers were published 8-74 (33.7 ± 17.33) months after thesis submission; the postgraduate student was first author in papers from 26 (54%) of the published theses. Gender of the student, department of origin, year of thesis submission, hierarchy of the supervisor, number and department of co-supervisors, and thesis characteristics did not influence publication rates. Conclusions: Rate of publication in indexed journals, of papers derived from postgraduate theses is 30%. In this study we were unable to identify factors that promote publication. PMID:20195030

Multi-terminology indexing for the assignment of MeSH descriptors to medical abstracts in French.

PubMed

Pereira, Suzanne; Sakji, Saoussen; Névéol, Aurélie; Kergourlay, Ivan; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J

2009-11-14

To facilitate information retrieval in the biomedical domain, a system for the automatic assignment of Medical Subject Headings to documents curated by an online quality-controlled health gateway was implemented. The French Multi-Terminology Indexer (F-MTI) implements a multiterminology approach using nine main medical terminologies in French and the mappings between them. This paper presents recent efforts to assess the added value of (a) integrating four new terminologies (Orphanet, ATC, drug names, MeSH supplementary concepts) into F-MTI's knowledge sources and (b) performing the automatic indexing on the titles and abstracts (vs. title only) of the online health resources. F-MTI was evaluated on a CISMeF corpus comprising 18,161 manually indexed resources. The performance of F-MTI including nine health terminologies on CISMeF resources with Title only was 27.9% precision and 19.7% recall, while the performance on CISMeF resources with Title and Abstract is 14.9 % precision (-13.0%) and 25.9% recall (+6.2%). In a few weeks, CISMeF will launch the indexing of resources based on title and abstract, using nine terminologies.

Tagline: Information Extraction for Semi-Structured Text Elements in Medical Progress Notes

ERIC Educational Resources Information Center

Finch, Dezon Kile

2012-01-01

Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in…

A comparative study of the origin, structure, and indexing language of the Persian and English keywords of articles indexed in the IranMedex database and their compliance with the Persian medical thesaurus and Medical Subject Headings

PubMed Central

Parsaei-Mohammadi, Parastoo; Ghasemi, Ali Hossein; Hassanzadeh-Beheshtabad, Raziyeh

2017-01-01

Introduction: In the present era, thesauri as tools in indexing play an effective role in integrating retrieval preventing fragmentation as well as a multiplicity of terminologies and also in providing information content of documents. Goals: This study aimed to investigate the keywords of articles indexed in IranMedex in terms of origin, structure and indexing situation and their Compliance with the Persian Medical Thesaurus and Medical Subject Headings (MeSH). Materials and Methods: This study is an applied research, and a survey has been conducted. Statistical population includes 32,850 Persian articles which are indexed in the IranMedex during the years 1385–1391. 379 cases were selected as sample of the study. Data collection was done using a checklist. In analyzing the findings, the SPSS Software were used. Findings: Although there was no significant difference in terms of indexing origin between the proportion of different types of the Persian and English keywords of articles indexed in the IranMedex, the compliance rates of the Persian and English keywords with the Persian medical thesaurus and MeSH were different in different years. In the meantime, the structure of keywords is leaning more towards phrase structure, and a single word structure and the majority of keywords are selected from the titles and abstracts. Conclusion: The authors’ familiarity with the thesauri and controlled tools causes homogeneity in assigning keywords and also provides more precise, faster, and easier retrieval of the keywords. It's suggested that a mixture of natural and control languages to be used in this database in order to reach more comprehensive results. PMID:28546967

A bottom-up approach to MEDLINE indexing recommendations.

PubMed

Jimeno-Yepes, Antonio; Wilkowski, Bartłomiej; Mork, James G; Van Lenten, Elizabeth; Fushman, Dina Demner; Aronson, Alan R

2011-01-01

MEDLINE indexing performed by the US National Library of Medicine staff describes the essence of a biomedical publication in about 14 Medical Subject Headings (MeSH). Since 2002, this task is assisted by the Medical Text Indexer (MTI) program. We present a bottom-up approach to MEDLINE indexing in which the abstract is searched for indicators for a specific MeSH recommendation in a two-step process. Supervised machine learning combined with triage rules improves sensitivity of recommendations while keeping the number of recommended terms relatively small. Improvement in recommendations observed in this work warrants further exploration of this approach to MTI recommendations on a larger set of MeSH headings.

MedTxting: Learning based and Knowledge Rich SMS-style Medical Text Contraction

PubMed Central

Liu, Feifan; Moosavinasab, Soheil; Houston, Thomas K.; Yu, Hong

2012-01-01

In mobile health (M-health), Short Message Service (SMS) has shown to improve disease related self-management and health service outcomes, leading to enhanced patient care. However, the hard limit on character size for each message limits the full value of exploring SMS communication in health care practices. To overcome this problem and improve the efficiency of clinical workflow, we developed an innovative system, MedTxting (available at http://medtxting.askhermes.org), which is a learning-based but knowledge-rich system that compresses medical texts in a SMS style. Evaluations on clinical questions and discharge summary narratives show that MedTxting can effectively compress medical texts with reasonable readability and noticeable size reduction. Findings in this work reveal potentials of MedTxting to the clinical settings, allowing for real-time and cost-effective communication, such as patient condition reporting, medication consulting, physicians connecting to share expertise to improve point of care. PMID:23304328

Disaster metrics: quantification of acute medical disasters in trauma-related multiple casualty events through modeling of the Acute Medical Severity Index.

PubMed

Bayram, Jamil D; Zuabi, Shawki

2012-04-01

The interaction between the acute medical consequences of a Multiple Casualty Event (MCE) and the total medical capacity of the community affected determines if the event amounts to an acute medical disaster. There is a need for a comprehensive quantitative model in MCE that would account for both prehospital and hospital-based acute medical systems, leading to the quantification of acute medical disasters. Such a proposed model needs to be flexible enough in its application to accommodate a priori estimation as part of the decision-making process and a posteriori evaluation for total quality management purposes. The concept proposed by de Boer et al in 1989, along with the disaster metrics quantitative models proposed by Bayram et al on hospital surge capacity and prehospital medical response, were used as theoretical frameworks for a new comprehensive model, taking into account both prehospital and hospital systems, in order to quantify acute medical disasters. A quantitative model called the Acute Medical Severity Index (AMSI) was developed. AMSI is the proportion of the Acute Medical Burden (AMB) resulting from the event, compared to the Total Medical Capacity (TMC) of the community affected; AMSI = AMB/TMC. In this model, AMB is defined as the sum of critical (T1) and moderate (T2) casualties caused by the event, while TMC is a function of the Total Hospital Capacity (THC) and the medical rescue factor (R) accounting for the hospital-based and prehospital medical systems, respectively. Qualitatively, the authors define acute medical disaster as "a state after any type of Multiple Casualty Event where the Acute Medical Burden (AMB) exceeds the Total Medical Capacity (TMC) of the community affected." Quantitatively, an acute medical disaster has an AMSI value of more than one (AMB / TMC > 1). An acute medical incident has an AMSI value of less than one, without the need for medical surge. An acute medical emergency has an AMSI value of less than one with

[Systematic Readability Analysis of Medical Texts on Websites of German University Clinics for General and Abdominal Surgery].

PubMed

Esfahani, B Janghorban; Faron, A; Roth, K S; Grimminger, P P; Luers, J C

2016-12-01

Background: Besides the function as one of the main contact points, websites of hospitals serve as medical information portals. As medical information texts should be understood by any patients independent of the literacy skills and educational level, online texts should have an appropriate structure to ease understandability. Materials and Methods: Patient information texts on websites of clinics for general surgery at German university hospitals (n = 36) were systematically analysed. For 9 different surgical topics representative medical information texts were extracted from each website. Using common readability tools and 5 different readability indices the texts were analysed concerning their readability and structure. The analysis was furthermore stratified in relation to geographical regions in Germany. Results: For the definite analysis the texts of 196 internet websites could be used. On average the texts consisted of 25 sentences and 368 words. The reading analysis tools congruously showed that all texts showed a rather low readability demanding a high literacy level from the readers. Conclusion: Patient information texts on German university hospital websites are difficult to understand for most patients. To fulfill the ambition of informing the general population in an adequate way about medical issues, a revision of most medical texts on websites of German surgical hospitals is recommended. Georg Thieme Verlag KG Stuttgart · New York.

Multi-terminology indexing for the assignment of MeSH descriptors to medical abstracts in French

PubMed Central

Pereira, Suzanne; Sakji, Saoussen; Névéol, Aurélie; Kergourlay, Ivan; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J.

2009-01-01

Background: To facilitate information retrieval in the biomedical domain, a system for the automatic assignment of Medical Subject Headings to documents curated by an online quality-controlled health gateway was implemented. The French Multi-Terminology Indexer (F-MTI) implements a multiterminology approach using nine main medical terminologies in French and the mappings between them. Objective: This paper presents recent efforts to assess the added value of (a) integrating four new terminologies (Orphanet, ATC, drug names, MeSH supplementary concepts) into F-MTI’s knowledge sources and (b) performing the automatic indexing on the titles and abstracts (vs. title only) of the online health resources. Methods: F-MTI was evaluated on a CISMeF corpus comprising 18,161 manually indexed resources. Results: The performance of F-MTI including nine health terminologies on CISMeF resources with Title only was 27.9% precision and 19.7% recall, while the performance on CISMeF resources with Title and Abstract is 14.9 % precision (−13.0%) and 25.9% recall (+6.2%). Conclusion: In a few weeks, CISMeF will launch the indexing of resources based on title and abstract, using nine terminologies. PMID:20351910

Implementation of Emergency Medical Text Classifier for Syndromic Surveillance

PubMed Central

Travers, Debbie; Haas, Stephanie W.; Waller, Anna E.; Schwartz, Todd A.; Mostafa, Javed; Best, Nakia C.; Crouch, John

2013-01-01

Public health officials use syndromic surveillance systems to facilitate early detection and response to infectious disease outbreaks. Emergency department clinical notes are becoming more available for surveillance but present the challenge of accurately extracting concepts from these text data. The purpose of this study was to implement a new system, Emergency Medical Text Classifier (EMT-C), into daily production for syndromic surveillance and evaluate system performance and user satisfaction. The system was designed to meet user preferences for a syndromic classifier that maximized positive predictive value and minimized false positives in order to provide a manageable workload. EMT-C performed better than the baseline system on all metrics and users were slightly more satisfied with it. It is vital to obtain user input and test new systems in the production environment. PMID:24551413

Implementation of Emergency Medical Text Classifier for syndromic surveillance.

PubMed

Travers, Debbie; Haas, Stephanie W; Waller, Anna E; Schwartz, Todd A; Mostafa, Javed; Best, Nakia C; Crouch, John

2013-01-01

Public health officials use syndromic surveillance systems to facilitate early detection and response to infectious disease outbreaks. Emergency department clinical notes are becoming more available for surveillance but present the challenge of accurately extracting concepts from these text data. The purpose of this study was to implement a new system, Emergency Medical Text Classifier (EMT-C), into daily production for syndromic surveillance and evaluate system performance and user satisfaction. The system was designed to meet user preferences for a syndromic classifier that maximized positive predictive value and minimized false positives in order to provide a manageable workload. EMT-C performed better than the baseline system on all metrics and users were slightly more satisfied with it. It is vital to obtain user input and test new systems in the production environment.

Impact factor of Korean Journal of Pediatrics on Korean Medical Citation Index and Science Citation Index of Web of Science

PubMed Central

Choi, Sun Hee; Han, Man Yong; Rha, Yeong Ho; Lee, Young Jin

2011-01-01

Purpose The total number of times a paper is cited, also known as the impact factor (IF) of a medical journal, is widely implied in evaluating the quality of a research paper. We evaluated the citation index data as an IF of Korean J Pediatr in Korean Medical Citation Index (KoMCI) and JCI of Web of Science. Methods We calculated the IF of Korean J Pediatr at KoMCI supervised by Korean Association of Medical Journal Editors. And we estimated the IF of Korean J Pediatr by the JCI of Web of Science although it was never officially reported. Results The IF of Korean J Pediatr on KoMCI has increased from 0.100 in the year 2000, to 0.205 in 2008, and 0.326 in 2009. Although the IF of Korean J Pediatr was 0.006 in 2005, 0.018 in 2006, 0.028 in 2008, 0.066 in 2009, and 0.018 in 2010 according to the JCI of Web of Science, the number of citations are steadily increasing. Conclusion Understanding and realizing the current status will be a stepping stone for further improvement. The next objective of the Korean J Pediatr is to become registered in the SCI or SCIE. Increasing the IF according to the JCI of Web of Science is crucial in order to achieve this goal. PMID:21738548

Impact factor of Korean Journal of Pediatrics on Korean Medical Citation Index and Science Citation Index of Web of Science.

PubMed

Bae, Chong Woo; Choi, Sun Hee; Han, Man Yong; Rha, Yeong Ho; Lee, Young Jin

2011-04-01

The total number of times a paper is cited, also known as the impact factor (IF) of a medical journal, is widely implied in evaluating the quality of a research paper. We evaluated the citation index data as an IF of Korean J Pediatr in Korean Medical Citation Index (KoMCI) and JCI of Web of Science. We calculated the IF of Korean J Pediatr at KoMCI supervised by Korean Association of Medical Journal Editors. And we estimated the IF of Korean J Pediatr by the JCI of Web of Science although it was never officially reported. The IF of Korean J Pediatr on KoMCI has increased from 0.100 in the year 2000, to 0.205 in 2008, and 0.326 in 2009. Although the IF of Korean J Pediatr was 0.006 in 2005, 0.018 in 2006, 0.028 in 2008, 0.066 in 2009, and 0.018 in 2010 according to the JCI of Web of Science, the number of citations are steadily increasing. Understanding and realizing the current status will be a stepping stone for further improvement. The next objective of the Korean J Pediatr is to become registered in the SCI or SCIE. Increasing the IF according to the JCI of Web of Science is crucial in order to achieve this goal.

Development and preliminary psychometric properties of a well-being index for medical students.

PubMed

Dyrbye, Liselotte N; Szydlo, Daniel W; Downing, Steven M; Sloan, Jeff A; Shanafelt, Tait D

2010-01-27

Psychological distress is common among medical students but manifests in a variety of forms. Currently, no brief, practical tool exists to simultaneously evaluate these domains of distress among medical students. The authors describe the development of a subject-reported assessment (Medical Student Well-Being Index, MSWBI) intended to screen for medical student distress across a variety of domains and examine its preliminary psychometric properties. Relevant domains of distress were identified, items generated, and a screening instrument formed using a process of literature review, nominal group technique, input from deans and medical students, and correlation analysis from previously administered assessments. Eleven experts judged the clarity, relevance, and representativeness of the items. A Content Validity Index (CVI) was calculated. Interrater agreement was assessed using pair-wise percent agreement adjusted for chance agreement. Data from 2248 medical students who completed the MSWBI along with validated full-length instruments assessing domains of interest was used to calculate reliability and explore internal structure validity. Burnout (emotional exhaustion and depersonalization), depression, mental quality of life (QOL), physical QOL, stress, and fatigue were domains identified for inclusion in the MSWBI. Six of 7 items received item CVI-relevance and CVI-representativeness of >or=0.82. Overall scale CVI-relevance and CVI-representativeness was 0.94 and 0.91. Overall pair-wise percent agreement between raters was >or=85% for clarity, relevance, and representativeness. Cronbach's alpha was 0.68. Item by item percent pair-wise agreements and Phi were low, suggesting little overlap between items. The majority of MSWBI items had a >or=74% sensitivity and specificity for detecting distress within the intended domain. The results of this study provide evidence of reliability and content-related validity of the MSWBI. Further research is needed to assess

Development and preliminary psychometric properties of a well-being index for medical students

PubMed Central

2010-01-01

Background Psychological distress is common among medical students but manifests in a variety of forms. Currently, no brief, practical tool exists to simultaneously evaluate these domains of distress among medical students. The authors describe the development of a subject-reported assessment (Medical Student Well-Being Index, MSWBI) intended to screen for medical student distress across a variety of domains and examine its preliminary psychometric properties. Methods Relevant domains of distress were identified, items generated, and a screening instrument formed using a process of literature review, nominal group technique, input from deans and medical students, and correlation analysis from previously administered assessments. Eleven experts judged the clarity, relevance, and representativeness of the items. A Content Validity Index (CVI) was calculated. Interrater agreement was assessed using pair-wise percent agreement adjusted for chance agreement. Data from 2248 medical students who completed the MSWBI along with validated full-length instruments assessing domains of interest was used to calculate reliability and explore internal structure validity. Results Burnout (emotional exhaustion and depersonalization), depression, mental quality of life (QOL), physical QOL, stress, and fatigue were domains identified for inclusion in the MSWBI. Six of 7 items received item CVI-relevance and CVI-representativeness of ≥0.82. Overall scale CVI-relevance and CVI-representativeness was 0.94 and 0.91. Overall pair-wise percent agreement between raters was ≥85% for clarity, relevance, and representativeness. Cronbach's alpha was 0.68. Item by item percent pair-wise agreements and Phi were low, suggesting little overlap between items. The majority of MSWBI items had a ≥74% sensitivity and specificity for detecting distress within the intended domain. Conclusions The results of this study provide evidence of reliability and content-related validity of the MSWBI. Further

Mobile phone text message reminders: Measuring preferences of people with antipsychotic medication.

PubMed

Kauppi, Kaisa; Kannisto, Kati A; Hätönen, Heli; Anttila, Minna; Löyttyniemi, Eliisa; Adams, Clive E; Välimäki, Maritta

2015-10-01

Mobile technology use, including Short Messaging Service (SMS) text messaging, has increased in health care services. Preferences regarding the type or timing of text messages sent by healthcare providers to people with antipsychotic medication have not yet been fully investigated. This study examines the relationship between patients' demographic characteristics and the tailored messages they select. The study ("Mobile.Net", 27704027) includes a structured analysis of a random sub-sample of participants who received messages for 12months. The data were collected in 24 sites and 45 psychiatric hospitals in Finland and analyzed with descriptive statistics and Poisson regression models. The study sample involved 562 people on antipsychotic medication, and a total of 2112 text messages (2 to 25 monthly) were analysed. Regarding message content, there was no significant variation in the proportions relating to 'medication', 'treatment appointments' or 'free time'. Monday was the most popular day to receive messages and morning was preferred to later in the day. Age was most closely associated with 'number of messages' and 'time of messages'. Older women and younger men preferred higher numbers of messages (p=0.0031). Participants preferred positive, encouraging and slightly humorous messages. The findings suggest that messages may be acceptable for difficult to access groups in follow-up. This type of intervention may be useful for various types of patients especially for younger males. To further support the evidence about factors related to message utilization and use, it is important to evaluate the effectiveness of text messages in psychiatric care. Copyright © 2015. Published by Elsevier B.V.

A Recent Advance in the Automatic Indexing of the Biomedical Literature

PubMed Central

Névéol, Aurélie; Shooshan, Sonya E.; Humphrey, Susanne M.; Mork, James G.; Aronson, Alan R.

2009-01-01

The volume of biomedical literature has experienced explosive growth in recent years. This is reflected in the corresponding increase in the size of MEDLINE®, the largest bibliographic database of biomedical citations. Indexers at the U.S. National Library of Medicine (NLM) need efficient tools to help them accommodate the ensuing workload. After reviewing issues in the automatic assignment of Medical Subject Headings (MeSH® terms) to biomedical text, we focus more specifically on the new subheading attachment feature for NLM’s Medical Text Indexer (MTI). Natural Language Processing, statistical, and machine learning methods of producing automatic MeSH main heading/subheading pair recommendations were assessed independently and combined. The best combination achieves 48% precision and 30% recall. After validation by NLM indexers, a suitable combination of the methods presented in this paper was integrated into MTI as a subheading attachment feature producing MeSH indexing recommendations compliant with current state-of-the-art indexing practice. PMID:19166973

A recent advance in the automatic indexing of the biomedical literature.

PubMed

Névéol, Aurélie; Shooshan, Sonya E; Humphrey, Susanne M; Mork, James G; Aronson, Alan R

2009-10-01

The volume of biomedical literature has experienced explosive growth in recent years. This is reflected in the corresponding increase in the size of MEDLINE, the largest bibliographic database of biomedical citations. Indexers at the US National Library of Medicine (NLM) need efficient tools to help them accommodate the ensuing workload. After reviewing issues in the automatic assignment of Medical Subject Headings (MeSH terms) to biomedical text, we focus more specifically on the new subheading attachment feature for NLM's Medical Text Indexer (MTI). Natural Language Processing, statistical, and machine learning methods of producing automatic MeSH main heading/subheading pair recommendations were assessed independently and combined. The best combination achieves 48% precision and 30% recall. After validation by NLM indexers, a suitable combination of the methods presented in this paper was integrated into MTI as a subheading attachment feature producing MeSH indexing recommendations compliant with current state-of-the-art indexing practice.

The effects of acupoint-catgut embedment combined with medical treatment on the BODE index scores of chronic obstructive pulmonary disease (COPD) patients

NASA Astrophysics Data System (ADS)

Giri, P. B. S. W.; Srilestari, A.; Abdurrohim, K.; Yunus, F.

2017-08-01

Chronic Obstructive Pulmonary Disease (COPD) is now the fourth leading cause of death in the world. As COPD medications are associated with high mortality levels, continuous research into the improvement of treatment modalities is being conducted. This study aimed to identify the effects of acupoint-catgut embedment combined with medical treatment on the Body mass index, airflow Obstruction, Dyspnea and Exercise capacity (BODE) index scores of COPD patients. A single-blind randomized controlled trial was conducted on 48 patients; participants were allocated into either the acupoint-catgut embedment with medication group (case group) or the sham acupuncture with medication group (control group). Acupoint-catgut embedment was conducted at the BL13 Feishu, BL43 Gaohuangshu, BL20 Pishu, BL23 Shenshu, and ST40 Fenglong points two times at an interval of 15 days. The BODE index, a primary outcome indicator, was assessed on Day 1 and Day 30. The results showed statistically and clinically significant differences between the two groups—in fact, BODE index scores were reduced by 1.83 points in the case group (p = 0.000). Ultimately, BODE index scores were lower in the intervention group than in the control group, thus indicating a statistically significant and clinically important improvement of COPD-related symptoms. According to these results, acupoint-catgut embedment combined with medical treatment is concluded to be more effective than medical treatment alone in reducing BODE index scores.

Psychometric properties of the Medical Student Well-Being Index among medical students in a Malaysian medical school.

PubMed

Yusoff, Muhamad Saiful Bahri; Yaacob, Mohd Jamil; Naing, Nyi Nyi; Esa, Ab Rahman

2013-02-01

This study evaluated the convergent, discriminant, construct, concurrent and discriminative validity of the Medical Student Wellbeing Index (MSWBI) as well as to evaluate its internal consistency and optimal cut-off total scores to detect at least moderate levels of general psychological distress, stress, anxiety and depression symptoms. A cross sectional study was done on 171 medical students. The MSWBI and DASS-21 were administered and returned immediately upon completion. Confirmatory factor analysis, reliability analysis, ROC analysis and Pearson correlation test were applied to assess psychometric properties of the MSWBI. A total of 168 (98.2%) medical students responded. The goodness of fit indices showed the MSWBI had a good construct (χ(2)=6.14, p=0.803, RMSEA<0.001, RMR=0.004, GFI=0.99, AGFI=0.97, CFI=1.00, IFI=1.02, TLI=1.04). The Cronbach's alpha value was 0.69 indicating an acceptable level of internal consistency. Pearson correlation coefficients and ROC analysis suggested each MSWBI's item showed adequate convergent and discriminant validity. Its optimal cut-off scores to detect at least moderate levels of general psychological distress, stress, anxiety, and depression were 1.5, 2.5, 1.5 and 2.5 respectively with sensitivity and specificity ranged from 62 to 80% and the areas under ROC curve ranged from 0.71 to 0.83. This study showed that the MSWBI had good level of psychometric properties. The MSWBI score more than 2 can be considered as having significant psychological distress. The MSWBI is a valid and reliable screening instrument to assess psychological distress of medical students. Copyright © 2012 Elsevier B.V. All rights reserved.

Text-message reminders plus incentives increase adherence to antidiabetic medication in adults with type 2 diabetes.

PubMed

Raiff, Bethany R; Jarvis, Brantley P; Dallery, Jesse

2016-12-01

Some adults with Type 2 diabetes mellitus have difficulty adhering to their oral medication regimens. The current study used a multiple baseline design with 3 adults with Type 2 diabetes. Medication taking was monitored remotely in real time via an electronic pill bottle. During the intervention, monetary incentives were delivered contingent on evidence of adherence to taking medication at specified times. Text-message reminders were also sent if medication was not taken. Adherence increased for all participants. Future studies should separate the relative contributions of text-message and incentive components of the intervention. © 2016 Society for the Experimental Analysis of Behavior.

Quality performance measurement using the text of electronic medical records.

PubMed

Pakhomov, Serguei; Bjornsen, Susan; Hanson, Penny; Smith, Steven

2008-01-01

Annual foot examinations (FE) constitute a critical component of care for diabetes. Documented evidence of FE is central to quality-of-care reporting; however, manual abstraction of electronic medical records (EMR) is slow, expensive, and subject to error. The objective of this study was to test the hypothesis that text mining of the EMR results in ascertaining FE evidence with accuracy comparable to manual abstraction. The text of inpatient and outpatient clinical reports was searched with natural-language (NL) queries for evidence of neurological, vascular, and structural components of FE. A manual medical records audit was used for validation. The reference standard consisted of 3 independent sets used for development (n=200 ), validation (n=118), and reliability (n=80). The reliability of manual auditing was 91% (95% confidence interval [CI]= 85-97) and was determined by comparing the results of an additional audit to the original audit using the records in the reliability set. The accuracy of the NL query requiring 1 of 3 FE components was 89% (95% CI=83-95). The accuracy of the query requiring any 2 of 3 components was 88% (95% CI=82-94). The accuracy of the query requiring all 3 components was 75% (95% CI= 68- 83). The free text of the EMR is a viable source of information necessary for quality of health care reporting on the evidence of FE for patients with diabetes. The low-cost methodology is scalable to monitoring large numbers of patients and can be used to streamline quality-of-care reporting.

Indexing method of digital audiovisual medical resources with semantic Web integration.

PubMed

Cuggia, Marc; Mougin, Fleur; Le Beux, Pierre

2003-01-01

Digitalization of audio-visual resources combined with the performances of the networks offer many possibilities which are the subject of intensive work in the scientific and industrial sectors. Indexing such resources is a major challenge. Recently, the Motion Pictures Expert Group (MPEG) has been developing MPEG-7, a standard for describing multimedia content. The good of this standard is to develop a rich set of standardized tools to enable fast efficient retrieval from digital archives or filtering audiovisual broadcasts on the internet. How this kind of technologies could be used in the medical context? In this paper, we propose a simpler indexing system, based on Dublin Core standard and complaint to MPEG-7. We use MeSH and UMLS to introduce conceptual navigation. We also present a video-platform with enables to encode and give access to audio-visual resources in streaming mode.

Indexing method of digital audiovisual medical resources with semantic Web integration.

PubMed

Cuggia, Marc; Mougin, Fleur; Le Beux, Pierre

2005-03-01

Digitalization of audiovisual resources and network capability offer many possibilities which are the subject of intensive work in scientific and industrial sectors. Indexing such resources is a major challenge. Recently, the Motion Pictures Expert Group (MPEG) has developed MPEG-7, a standard for describing multimedia content. The goal of this standard is to develop a rich set of standardized tools to enable efficient retrieval from digital archives or the filtering of audiovisual broadcasts on the Internet. How could this kind of technology be used in the medical context? In this paper, we propose a simpler indexing system, based on the Dublin Core standard and compliant to MPEG-7. We use MeSH and the UMLS to introduce conceptual navigation. We also present a video-platform which enables encoding and gives access to audiovisual resources in streaming mode.

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue.

PubMed

Pereira, Suzanne; Névéol, Aurélie; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J

2008-11-06

To assist with the development of a French online quality-controlled health gateway(CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (FMTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them. In this paper,we compare lemmatization and stemming as methods to process French medical text for indexing. We also evaluate the multi-terminology approach implemented in F-MTI. The indexing strategies were assessed on a corpus of 18,814 resources indexed manually. There is little difference in the indexing performance when lemmatization or stemming is used. However, the multi-terminology approach outperforms indexing relying on a single terminology in terms of recall. F-MTI will soon be used in the CISMeF production environment and in a Health MultiTerminology Server in French.

Using the NASA Task Load Index to Assess Workload in Electronic Medical Records.

PubMed

Hudson, Darren; Kushniruk, Andre W; Borycki, Elizabeth M

2015-01-01

Electronic medical records (EMRs) has been expected to decrease health professional workload. The NASA Task Load Index has become an important tool for assessing workload in many domains. However, its application in assessing the impact of an EMR on nurse's workload has remained to be explored. In this paper we report the results of a study of workload and we explore the utility of applying the NASA Task Load Index to assess impact of an EMR at the end of its lifecycle on nurses' workload. It was found that mental and temporal demands were the most responsible for the workload. Further work along these lines is recommended.

Comparing a medical records-based and a claims-based index for measuring comorbidity in patients with lung or colon cancer.

PubMed

Kehl, Kenneth L; Lamont, Elizabeth B; McNeil, Barbara J; Bozeman, Samuel R; Kelley, Michael J; Keating, Nancy L

2015-05-01

Ascertaining comorbid conditions in cancer patients is important for research and clinical quality measurement, and is particularly important for understanding care and outcomes for older patients and those with multi-morbidity. We compared the medical records-based ACE-27 index and the claims-based Charlson index in predicting receipt of therapy and survival for lung and colon cancer patients. We calculated the Charlson index using administrative data and the ACE-27 score using medical records for Veterans Affairs patients diagnosed with stage I/II non-small cell lung or stage III colon cancer from January 2003 to December 2004. We compared the proportion of patients identified by each index as having any comorbidity. We used multivariable logistic regression to ascertain the predictive power of each index regarding delivery of guideline-recommended therapies and two-year survival, comparing the c-statistic and the Akaike information criterion (AIC). Overall, 97.2% of lung and 90.9% of colon cancer patients had any comorbidity according to the ACE-27 index, versus 59.5% and 49.7%, respectively, according to the Charlson. Multivariable models including the ACE-27 index outperformed Charlson-based models when assessing receipt of guideline-recommended therapies, with higher c-statistics and lower AICs. Neither index was clearly superior in prediction of two-year survival. The ACE-27 index measured using medical records captured more comorbidity and outperformed the Charlson index measured using administrative data for predicting receipt of guideline-recommended therapies, demonstrating the potential value of more detailed comorbidity data. However, the two indices had relatively similar performance when predicting survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation of a French medical multi-terminology indexer for the manual annotation of natural language medical reports of healthcare-associated infections.

PubMed

Sakji, Saoussen; Gicquel, Quentin; Pereira, Suzanne; Kergourlay, Ivan; Proux, Denys; Darmoni, Stéfan; Metzger, Marie-Hélène

2010-01-01

Surveillance of healthcare-associated infections is essential to prevention. A new collaborative project, namely ALADIN, was launched in January 2009 and aims to develop an automated detection tool based on natural language processing of medical documents. The objective of this study was to evaluate the annotation of natural language medical reports of healthcare-associated infections. A software MS Access application (NosIndex) has been developed to interface ECMT XML answer and manual annotation work. ECMT performances were evaluated by an infection control practitioner (ICP). Precision was evaluated for the 2 modules and recall only for the default module. Exclusion rate was defined as ratio between medical terms not found by ECMT and total number of terms evaluated. The medical discharge summaries were randomly selected in 4 medical wards. From the 247 medical terms evaluated, ECMT proposed 428 and 3,721 codes, respectively for the default and expansion modules. The precision was higher with the default module (P1=0.62) than with the expansion (P2=0.47). Performances of ECMT as support tool for the medical annotation were satisfactory.

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue

PubMed Central

Pereira, Suzanne; Névéol, Aurélie; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J.

2008-01-01

Background: To assist with the development of a French online quality-controlled health gateway (CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (F-MTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them. Objective: In this paper, we compare lemmatization and stemming as methods to process French medical text for indexing. We also evaluate the multi-terminology approach implemented in F-MTI. Methods: The indexing strategies were assessed on a corpus of 18,814 resources indexed manually. Results: There is little difference in the indexing performance when lemmatization or stemming is used. However, the multi-terminology approach outperforms indexing relying on a single terminology in terms of recall. Conclusion: F-MTI will soon be used in the CISMeF production environment and in a Health MultiTerminology Server in French. PMID:18998933

Principle and engineering implementation of 3D visual representation and indexing of medical diagnostic records (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shi, Liehang; Sun, Jianyong; Yang, Yuanyuan; Ling, Tonghui; Wang, Mingqing; Zhang, Jianguo

2017-03-01

Purpose: Due to the generation of a large number of electronic imaging diagnostic records (IDR) year after year in a digital hospital, The IDR has become the main component of medical big data which brings huge values to healthcare services, professionals and administration. But a large volume of IDR presented in a hospital also brings new challenges to healthcare professionals and services as there may be too many IDRs for each patient so that it is difficult for a doctor to review all IDR of each patient in a limited appointed time slot. In this presentation, we presented an innovation method which uses an anatomical 3D structure object visually to represent and index historical medical status of each patient, which is called Visual Patient (VP) in this presentation, based on long term archived electronic IDR in a hospital, so that a doctor can quickly learn the historical medical status of the patient, quickly point and retrieve the IDR he or she interested in a limited appointed time slot. Method: The engineering implementation of VP was to build 3D Visual Representation and Index system called VP system (VPS) including components of natural language processing (NLP) for Chinese, Visual Index Creator (VIC), and 3D Visual Rendering Engine.There were three steps in this implementation: (1) an XML-based electronic anatomic structure of human body for each patient was created and used visually to index the all of abstract information of each IDR for each patient; (2)a number of specific designed IDR parsing processors were developed and used to extract various kinds of abstract information of IDRs retrieved from hospital information systems; (3) a 3D anatomic rendering object was introduced visually to represent and display the content of VIO for each patient. Results: The VPS was implemented in a simulated clinical environment including PACS/RIS to show VP instance to doctors. We setup two evaluation scenario in a hospital radiology department to evaluate whether

'Working is out of the question': a qualitative text analysis of medical certificates of disability.

PubMed

Aarseth, Guri; Natvig, Bård; Engebretsen, Eivind; Lie, Anne Kveim

2017-04-20

Medical certificates influence the distribution of economic benefits in welfare states; however, the qualitative aspects of these texts remain largely unexplored. The present study is the first systematic investigation done of these texts. Our aim was to investigate how GPs select and mediate information about their patients' health and how they support their conclusions about illness, functioning and fitness for work in medical certificates. We performed a textual analysis of thirty-three medical certificates produced by general practitioners (GP) in Norway at the request of the Norwegian Labour and Welfare Administration (NAV).The certificates were subjected to critical reading using the combined analytic methods of narratology and linguistics. Some of the medical information was unclear, ambiguous, and possibly misleading. Evaluations of functioning related to illness were scarce or absent, regardless of diagnosis, and, hence, the basis of working incapacity was unclear. Voices in the text frequently conflated, obscuring the source of speaker. In some documents, the expert's subtle use of language implied doubts about the claimant's credibility, but explicit advocacy also occurred. GPs show little insight into their patients' working lives, but rather than express uncertainty and incompetence, they may resort to making too absolute and too general statements about patients' working capacity, and fail to report thorough assessments. A number of the texts in our material may not function as sufficient or reliable sources for making decisions regarding social benefits. Certificates as these may be deficient for several reasons, and textual incompetence may be one of them. Physicians in Norway receive no systematic training in professional writing. High-quality medical certificates, we believe, might be economical in the long term: it might increase the efficiency with which NAV processes cases and save costs by eliminating the need for unnecessary and expensive

Cross-cultural Adaptation and Validation of the Medication Regimen Complexity Index Adapted to Spanish.

PubMed

Saez de la Fuente, Javier; Such Diaz, Ana; Cañamares-Orbis, Irene; Ramila, Estela; Izquierdo-Garcia, Elsa; Esteban, Concepcion; Escobar-Rodríguez, Ismael

2016-11-01

The most widely used validated instrument to assess the complexity of medication regimens is the Medication Regimen Complexity Index (MRCI). This study aimed to translate, adapt, and validate a reliable version of the MRCI adapted to Spanish (MRCI-E). The cross-cultural adaptation process consisted of an independent translation by 3 clinical pharmacists and a backtranslation by 2 native English speakers. A reliability analysis was conducted on 20 elderly randomly selected patients. Two clinical pharmacists calculated the MRCI-E from discharge treatments and 2 months later. For the validity analysis, the sample was augmented to 60 patients. Convergent validity was assessed by analyzing the correlation between the number of medications; discriminant validity was stratified by gender; and predictive validity was determined by analyzing the ability to predict readmission and mortality at 3 and 6 months. The MRCI-E retained the original structure of 3 sections. The reliability analysis demonstrated an excellent internal consistency (Cronbach's α=0.83), and the intraclass correlation coefficient exceeded 0.9 in all cases. The correlation coefficient with the number of medications was 0.883 ( P<0.001). No significant differences were found when stratified by gender (3.6; 95%CI=-2.9 to 10.2; P=0.27). Patients who were readmitted at 3 months had a higher MRCI-E score (10.7; 95%CI=4.4 to 17.2; P=0.001). The differences remained significant in patients readmitted at 6 months, but differences in mortality were not detected. The MRCI-E retains the reliability and validity of the original index and provides a suitable tool to assess the complexity of medication regimens in Spanish.

A Novel Approach towards Medical Entity Recognition in Chinese Clinical Text

PubMed Central

Yu, Jian

2017-01-01

Medical entity recognition, a basic task in the language processing of clinical data, has been extensively studied in analyzing admission notes in alphabetic languages such as English. However, much less work has been done on nonstructural texts that are written in Chinese, or in the setting of differentiation of Chinese drug names between traditional Chinese medicine and Western medicine. Here, we propose a novel cascade-type Chinese medication entity recognition approach that aims at integrating the sentence category classifier from a support vector machine and the conditional random field-based medication entity recognition. We hypothesized that this approach could avoid the side effects of abundant negative samples and improve the performance of the named entity recognition from admission notes written in Chinese. Therefore, we applied this approach to a test set of 324 Chinese-written admission notes with manual annotation by medical experts. Our data demonstrated that this approach had a score of 94.2% in precision, 92.8% in recall, and 93.5% in F-measure for the recognition of traditional Chinese medicine drug names and 91.2% in precision, 92.6% in recall, and 91.7% F-measure for the recognition of Western medicine drug names. The differences in F-measure were significant compared with those in the baseline systems. PMID:29065612

Concept-match medical data scrubbing. How pathology text can be used in research.

PubMed

Berman, Jules J

2003-06-01

In the normal course of activity, pathologists create and archive immense data sets of scientifically valuable information. Researchers need pathology-based data sets, annotated with clinical information and linked to archived tissues, to discover and validate new diagnostic tests and therapies. Pathology records can be used for research purposes (without obtaining informed patient consent for each use of each record), provided the data are rendered harmless. Large data sets can be made harmless through 3 computational steps: (1) deidentification, the removal or modification of data fields that can be used to identify a patient (name, social security number, etc); (2) rendering the data ambiguous, ensuring that every data record in a public data set has a nonunique set of characterizing data; and (3) data scrubbing, the removal or transformation of words in free text that can be used to identify persons or that contain information that is incriminating or otherwise private. This article addresses the problem of data scrubbing. To design and implement a general algorithm that scrubs pathology free text, removing all identifying or private information. The Concept-Match algorithm steps through confidential text. When a medical term matching a standard nomenclature term is encountered, the term is replaced by a nomenclature code and a synonym for the original term. When a high-frequency "stop" word, such as a, an, the, or for, is encountered, it is left in place. When any other word is encountered, it is blocked and replaced by asterisks. This produces a scrubbed text. An open-source implementation of the algorithm is freely available. The Concept-Match scrub method transformed pathology free text into scrubbed output that preserved the sense of the original sentences, while it blocked terms that did not match terms found in the Unified Medical Language System (UMLS). The scrubbed product is safe, in the restricted sense that the output retains only standard medical

Fine-grained indexing of the biomedical literature: MeSH subheading attachment for a MEDLINE indexing tool.

PubMed

Névéol, Aurélie; Shooshan, Sonya E; Mork, James G; Aronson, Alan R

2007-10-11

This paper reports on the latest results of an Indexing Initiative effort addressing the automatic attachment of subheadings to MeSH main headings recommended by the NLM's Medical Text Indexer. Several linguistic and statistical approaches are used to retrieve and attach the subheadings. Continuing collaboration with NLM indexers also provided insight on how automatic methods can better enhance indexing practice. The methods were evaluated on corpus of 50,000 MEDLINE citations. For main heading/subheading pair recommendations, the best precision is obtained with a post-processing rule method (58%) while the best recall is obtained by pooling all methods (64%). For stand-alone subheading recommendations, the best performance is obtained with the PubMed Related Citations algorithm. Significant progress has been made in terms of subheading coverage. After further evaluation, some of this work may be integrated in the MEDLINE indexing workflow.

Use of General-purpose Negation Detection to Augment Concept Indexing of Medical Documents

PubMed Central

Mutalik, Pradeep G.; Deshpande, Aniruddha; Nadkarni, Prakash M.

2001-01-01

Objectives: To test the hypothesis that most instances of negated concepts in dictated medical documents can be detected by a strategy that relies on tools developed for the parsing of formal (computer) languages—specifically, a lexical scanner (“lexer”) that uses regular expressions to generate a finite state machine, and a parser that relies on a restricted subset of context-free grammars, known as LALR(1) grammars. Methods: A diverse training set of 40 medical documents from a variety of specialties was manually inspected and used to develop a program (Negfinder) that contained rules to recognize a large set of negated patterns occurring in the text. Negfinder's lexer and parser were developed using tools normally used to generate programming language compilers. The input to Negfinder consisted of medical narrative that was preprocessed to recognize UMLS concepts: the text of a recognized concept had been replaced with a coded representation that included its UMLS concept ID. The program generated an index with one entry per instance of a concept in the document, where the presence or absence of negation of that concept was recorded. This information was used to mark up the text of each document by color-coding it to make it easier to inspect. The parser was then evaluated in two ways: 1) a test set of 60 documents (30 discharge summaries, 30 surgical notes) marked-up by Negfinder was inspected visually to quantify false-positive and false-negative results; and 2) a different test set of 10 documents was independently examined for negatives by a human observer and by Negfinder, and the results were compared. Results: In the first evaluation using marked-up documents, 8,358 instances of UMLS concepts were detected in the 60 documents, of which 544 were negations detected by the program and verified by human observation (true-positive results, or TPs). Thirteen instances were wrongly flagged as negated (false-positive results, or FPs), and the program missed

[Influence of journals indexed by Science Citation Index (SCI) on Chinese medical journals based on the data of published articles by Chinese authors from 2000 - 2009].

PubMed

Fu, Xiao-Xia; Li, Gui-Cun

2011-04-01

This study was designed to investigate the influence of journals indexed by Science Citation Index (SCI) on Chinese medical journals. Articles on medicine written by Chinese and the journals that published these articles from 2000 to 2009 were searched using Science Citation Index Expanded (SCI-E) database, and the status and variation tendency of the impact factors (IF) of these journals were analyzed. Data of articles on medicine included Chinese Scientific and Technical Paper and Citations Data (CSTPCD) from 2000 to 2008 were searched (the data of 2009 have not been released). The included articles and the time-dependent changing profile were studied. These outcomes were evaluated as the fixed base relative or link relative when compared with the data of 2000 or those of last year, respectively. Geometric mean was used when mean increase was calculated and IF distribution was described with median. Totally 3774 articles from China were published by journals indexed by SCI-E in 2000, and the number of articles published by Chinese authors increased every year. In 2008, 16 714 articles were indexed by SCI-E, 442.87% higher than those of 2000. The increment was 161.54% higher than that of articles published in the journals indexed by CSTPCD (281.33%) during the same period. From 2000 to 2009, the geometric mean of increase in the number of published articles from China in journals indexed by SCI-E was 20.87% but it was 18.21% in CSTPCD. From 2000 to 2009, the median of IF of SCI-E indexed journals that published Chinese medical articles was 1.866, 2.073, 2.390, 2.702, 2.409, 2.496, 2.380, 2.218, 2.280 and 2.331, respectively, and they did not increase or even decreased. The number of the articles indexed by SCI-E increased year by year, much faster than that of CSTPCD. However, it does not necessarily mean the increase in impact.

Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator.

PubMed

Tchechmedjiev, Andon; Abdaoui, Amine; Emonet, Vincent; Melzi, Soumia; Jonnagaddala, Jitendra; Jonquet, Clement

2018-06-01

Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed for biomedical data, but not very suitable for clinical text annotation. In order to add new functionalities to the NCBO Annotator without hosting or modifying the original Web service, we have designed a proxy architecture that enables seamless extensions by pre-processing of the input text and parameters, and post processing of the annotations. We have then implemented enhanced functionalities for annotating and indexing free text such as: scoring, detection of context (negation, experiencer, temporality), new output formats and coarse-grained concept recognition (with UMLS Semantic Groups). In this paper, we present the NCBO Annotator+, a Web service which incorporates these new functionalities as well as a small set of evaluation results for concept recognition and clinical context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014). The Annotator+ has been successfully integrated into the SIFR BioPortal platform-an implementation of NCBO BioPortal for French biomedical terminologies and ontologies-to annotate English text. A Web user interface is available for testing and ontology selection (http://bioportal.lirmm.fr/ncbo_annotatorplus); however the Annotator+ is meant to be used through the Web service application programming interface (http://services.bioportal.lirmm.fr/ncbo_annotatorplus). The code is openly available, and we also provide a Docker packaging to enable easy local deployment to process sensitive (e.g. clinical) data in-house (https://github.com/sifrproject). andon.tchechmedjiev@lirmm.fr. Supplementary data are available at Bioinformatics online.

World Biomedical Journals, 1951-60: A Study of the Relative Significance of 1,388 Titles Indexed in Current List of Medical Literature*

PubMed Central

Raisig, L. Miles

1966-01-01

This study is an application of the relationship of serial articles published to serial articles cited, developed in theory in the author's “Statistical Bibliography in the Health Sciences” (Bulletin 50: 450-461, July 1962). A ranked list of the indexes of significance of most of the serials indexed in Current List of Medical Literature was derived and erected from 21,000 citations secured in a random sampling of 1962 and 1961 biomedical journals regularly received in the Yale Medical Library. The author measures the gross indexing effectiveness of Current List against his indexes of significance, offers his method and results as means to reach objective standards for indexing and abstracting, and projects his results as measures of general value of the serials analyzed. PMID:5952248

Knowledge requirements for automated inference of medical textbook markup.

PubMed Central

Berrios, D. C.; Kehler, A.; Fagan, L. M.

1999-01-01

Indexing medical text in journals or textbooks requires a tremendous amount of resources. We tested two algorithms for automatically indexing nouns, noun-modifiers, and noun phrases, and inferring selected binary relations between UMLS concepts in a textbook of infectious disease. Sixty-six percent of nouns and noun-modifiers and 81% of noun phrases were correctly matched to UMLS concepts. Semantic relations were identified with 100% specificity and 94% sensitivity. For some medical sub-domains, these algorithms could permit expeditious generation of more complex indexing. PMID:10566445

Fine-Grained Indexing of the Biomedical Literature: MeSH Subheading Attachment for a MEDLINE Indexing Tool

PubMed Central

Névéol, Aurélie; Shooshan, Sonya E.; Mork, James G.; Aronson, Alan R.

2007-01-01

Objective This paper reports on the latest results of an Indexing Initiative effort addressing the automatic attachment of subheadings to MeSH main headings recommended by the NLM’s Medical Text Indexer. Material and Methods Several linguistic and statistical approaches are used to retrieve and attach the subheadings. Continuing collaboration with NLM indexers also provided insight on how automatic methods can better enhance indexing practice. Results The methods were evaluated on corpus of 50,000 MEDLINE citations. For main heading/subheading pair recommendations, the best precision is obtained with a post-processing rule method (58%) while the best recall is obtained by pooling all methods (64%). For stand-alone subheading recommendations, the best performance is obtained with the PubMed Related Citations algorithm. Conclusion Significant progress has been made in terms of subheading coverage. After further evaluation, some of this work may be integrated in the MEDLINE indexing workflow. PMID:18693897

The Effectiveness of Mobile Phone Text Messaging in Improving Medication Adherence for Patients with Chronic Diseases: A Systematic Review.

PubMed

Ershad Sarabi, Roghayeh; Sadoughi, Farahnaz; Jamshidi Orak, Roohangiz; Bahaadinbeigy, Kambiz

2016-05-01

Medication non-adherence is a commonly observed problem in the self-administration of treatment, regardless of the disease type. Text messaging reminders, as electronic reminders, provide an opportunity to improve medication adherence. In this study, we aimed to provide evidence addressing the question of whether text message reminders were effective in improving patients' adherence to medication. We carried out a systematic literature search, using the five electronic bibliographic databases: PubMed, Embase, PsycINFO, CINAHL, and the Cochrane central register of controlled trials. Studies were included on the basis of whether they examined the benefits and effects of short-message service (SMS) interventions on medication adherence. The results of this systematic review indicated that text messaging interventions have improved patients' medication adherence rate (85%, 29.34). Included in the review, those who had problems with adherence, or those whom text messaging was most helpful had HIV, asthma, diabetes, schizophrenia and heart disease (73.5%). The period of intervention varied from 1 week to 14 months. The most common study design was randomized controlled trials (RCTs) (66%) carried out in the developed countries. This study demonstrated the potential of mobile phone text messaging for medication non-adherence problem solving.

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Prospects and limitations of full-text index structures in genome analysis

PubMed Central

Vyverman, Michaël; De Baets, Bernard; Fack, Veerle; Dawyndt, Peter

2012-01-01

The combination of incessant advances in sequencing technology producing large amounts of data and innovative bioinformatics approaches, designed to cope with this data flood, has led to new interesting results in the life sciences. Given the magnitude of sequence data to be processed, many bioinformatics tools rely on efficient solutions to a variety of complex string problems. These solutions include fast heuristic algorithms and advanced data structures, generally referred to as index structures. Although the importance of index structures is generally known to the bioinformatics community, the design and potency of these data structures, as well as their properties and limitations, are less understood. Moreover, the last decade has seen a boom in the number of variant index structures featuring complex and diverse memory-time trade-offs. This article brings a comprehensive state-of-the-art overview of the most popular index structures and their recently developed variants. Their features, interrelationships, the trade-offs they impose, but also their practical limitations, are explained and compared. PMID:22584621

Manual versus automated coding of free-text self-reported medication data in the 45 and Up Study: a validation study.

PubMed

Gnjidic, Danijela; Pearson, Sallie-Anne; Hilmer, Sarah N; Basilakis, Jim; Schaffer, Andrea L; Blyth, Fiona M; Banks, Emily

2015-03-30

Increasingly, automated methods are being used to code free-text medication data, but evidence on the validity of these methods is limited. To examine the accuracy of automated coding of previously keyed in free-text medication data compared with manual coding of original handwritten free-text responses (the 'gold standard'). A random sample of 500 participants (475 with and 25 without medication data in the free-text box) enrolled in the 45 and Up Study was selected. Manual coding involved medication experts keying in free-text responses and coding using Anatomical Therapeutic Chemical (ATC) codes (i.e. chemical substance 7-digit level; chemical subgroup 5-digit; pharmacological subgroup 4-digit; therapeutic subgroup 3-digit). Using keyed-in free-text responses entered by non-experts, the automated approach coded entries using the Australian Medicines Terminology database and assigned corresponding ATC codes. Based on manual coding, 1377 free-text entries were recorded and, of these, 1282 medications were coded to ATCs manually. The sensitivity of automated coding compared with manual coding was 79% (n = 1014) for entries coded at the exact ATC level, and 81.6% (n = 1046), 83.0% (n = 1064) and 83.8% (n = 1074) at the 5, 4 and 3-digit ATC levels, respectively. The sensitivity of automated coding for blank responses was 100% compared with manual coding. Sensitivity of automated coding was highest for prescription medications and lowest for vitamins and supplements, compared with the manual approach. Positive predictive values for automated coding were above 95% for 34 of the 38 individual prescription medications examined. Automated coding for free-text prescription medication data shows very high to excellent sensitivity and positive predictive values, indicating that automated methods can potentially be useful for large-scale, medication-related research.

Automatic extraction of relations between medical concepts in clinical texts

PubMed Central

Harabagiu, Sanda; Roberts, Kirk

2011-01-01

Objective A supervised machine learning approach to discover relations between medical problems, treatments, and tests mentioned in electronic medical records. Materials and methods A single support vector machine classifier was used to identify relations between concepts and to assign their semantic type. Several resources such as Wikipedia, WordNet, General Inquirer, and a relation similarity metric inform the classifier. Results The techniques reported in this paper were evaluated in the 2010 i2b2 Challenge and obtained the highest F1 score for the relation extraction task. When gold standard data for concepts and assertions were available, F1 was 73.7, precision was 72.0, and recall was 75.3. F1 is defined as 2*Precision*Recall/(Precision+Recall). Alternatively, when concepts and assertions were discovered automatically, F1 was 48.4, precision was 57.6, and recall was 41.7. Discussion Although a rich set of features was developed for the classifiers presented in this paper, little knowledge mining was performed from medical ontologies such as those found in UMLS. Future studies should incorporate features extracted from such knowledge sources, which we expect to further improve the results. Moreover, each relation discovery was treated independently. Joint classification of relations may further improve the quality of results. Also, joint learning of the discovery of concepts, assertions, and relations may also improve the results of automatic relation extraction. Conclusion Lexical and contextual features proved to be very important in relation extraction from medical texts. When they are not available to the classifier, the F1 score decreases by 3.7%. In addition, features based on similarity contribute to a decrease of 1.1% when they are not available. PMID:21846787

[A customized method for information extraction from unstructured text data in the electronic medical records].

PubMed

Bao, X Y; Huang, W J; Zhang, K; Jin, M; Li, Y; Niu, C Z

2018-04-18

There is a huge amount of diagnostic or treatment information in electronic medical record (EMR), which is a concrete manifestation of clinicians actual diagnosis and treatment details. Plenty of episodes in EMRs, such as complaints, present illness, past history, differential diagnosis, diagnostic imaging, surgical records, reflecting details of diagnosis and treatment in clinical process, adopt Chinese description of natural language. How to extract effective information from these Chinese narrative text data, and organize it into a form of tabular for analysis of medical research, for the practical utilization of clinical data in the real world, is a difficult problem in Chinese medical data processing. Based on the EMRs narrative text data in a tertiary hospital in China, a customized information extracting rules learning, and rule based information extraction methods is proposed. The overall method consists of three steps, which includes: (1) Step 1, a random sample of 600 copies (including the history of present illness, past history, personal history, family history, etc.) of the electronic medical record data, was extracted as raw corpora. With our developed Chinese clinical narrative text annotation platform, the trained clinician and nurses marked the tokens and phrases in the corpora which would be extracted (with a history of diabetes as an example). (2) Step 2, based on the annotated corpora clinical text data, some extraction templates were summarized and induced firstly. Then these templates were rewritten using regular expressions of Perl programming language, as extraction rules. Using these extraction rules as basic knowledge base, we developed extraction packages in Perl, for extracting data from the EMRs text data. In the end, the extracted data items were organized in tabular data format, for later usage in clinical research or hospital surveillance purposes. (3) As the final step of the method, the evaluation and validation of the proposed

Mobile phone text messaging to improve medication adherence in secondary prevention of cardiovascular disease.

PubMed

Adler, Alma J; Martin, Nicole; Mariani, Javier; Tajer, Carlos D; Owolabi, Onikepe O; Free, Caroline; Serrano, Norma C; Casas, Juan P; Perel, Pablo

2017-04-29

Worldwide at least 100 million people are thought to have prevalent cardiovascular disease (CVD). This population has a five times greater chance of suffering a recurrent cardiovascular event than people without known CVD. Secondary CVD prevention is defined as action aimed to reduce the probability of recurrence of such events. Drug interventions have been shown to be cost-effective in reducing this risk and are recommended in international guidelines. However, adherence to recommended treatments remains sub-optimal. In order to influence non-adherence, there is a need to develop scalable and cost-effective behaviour-change interventions. To assess the effects of mobile phone text messaging in patients with established arterial occlusive events on adherence to treatment, fatal and non-fatal cardiovascular events, and adverse effects. We searched CENTRAL, MEDLINE, Embase, the Conference Proceedings Citation Index - Science on Web of Science on 7 November 2016, and two clinical trial registers on 12 November 2016. We contacted authors of included studies for missing information and searched reference lists of relevant papers. We applied no language or date restrictions. We included randomised trials with at least 50% of the participants with established arterial occlusive events. We included trials investigating interventions using short message service (SMS) or multimedia messaging service (MMS) with the aim to improve adherence to medication for the secondary prevention of cardiovascular events. Eligible comparators were no intervention or other modes of communication. We used standard methodological procedures expected by Cochrane. In addition, we attempted to contact all authors on how the SMS were developed. We included seven trials (reported in 13 reports) with 1310 participants randomised. Follow-up ranged from one month to 12 months. Due to heterogeneity in the methods, population and outcome measures, we were unable to conduct meta-analysis on these studies

The Role of Surface, Semantic and Grammatical Features on Simplification of Spanish Medical Texts: A User Study

PubMed Central

Mukherjee, Partha; Leroy, Gondy; Kauchak, David; Navarrete, Brianda Armenta; Diaz, Damian Y.; Colina, Sonia

2017-01-01

Simplifying medical texts facilitates readability and comprehension. While most simplification work focuses on English, we investigate whether features important for simplifying English text are similarly helpful for simplifying Spanish text. We conducted a user study on 15 Spanish medical texts using Amazon Mechanical Turk and measured perceived and actual difficulty. Using the median of the difficulty scores, we split the texts into easy and difficult groups and extracted 10 surface, 2 semantic and 4 grammatical features. Using t-tests, we identified those features that significantly distinguish easy text from difficult text in Spanish and compare with prior work in English. We found that easy Spanish texts use more repeated words and adverbs, less negations and more familiar words, similar to English. Also like English, difficult Spanish texts use more nouns and adjectives. However in contrast to English, easier Spanish texts contained longer sentences and used grammatical structures that were more varied. PMID:29854201

Charlson Comorbidity Index, inappropriate medication use and cognitive impairment : Bermuda Triangle.

PubMed

Silay, Kamile; Yalcin, Ahmet; Akinci, Sema; Gursoy, Fatma Gul; Sener Dede, Didem

2017-11-01

The aim is to evaluate the association between the Charlson Comorbidity Index (CCI), polypharmacy, inappropriate medication use and cognitive impairment in long-term care facility patients. A cross-sectional study including 105 long-term care facility residents was performed. The Charlson Comorbidity Index (CCI) was used. Inappropriate drug use (IDU) was defined according to the STOPP (Screening Tool of Older People's Prescriptions) criteria. Univariate analysis to identify variables associated with patient outcome related with cognitive impairment was investigated with χ 2 , Pearson correlation, Fisher exact, and Mann-Whitney U test where appropriate. For the multivariate analysis, the possible factors identified with univariate analysis were further entered into logistic regression analysis. A significant difference was found between gender, CCI and cognitive impairment (p = 0.038, p = 0.01). While every one point increment in the CCI increases the risk of cognitive impairment 3.1 fold (95% CI = 1.8-5.4, p < 0.001), hypertension increases the risk 12 fold (95% CI = 2.5-67.8, p = 0.002). While the correlation between Mini-Mental Status Examination (MMSE) score and polypharmacy is significant (p = 0.015), the correlation between MMSE and IDU was insignificant (p = 0.739). The association of urogenital system drugs and dementia was significant (p = 0.044). Comorbidities, especially hypertension and old age, are risk factors for cognitive impairment. Polypharmacy correlates with MMSE and is considered a risk factor for cognitive impairment. Inappropriate medication use is high among long-term care facility residents. More studies on large cohorts are needed regarding optimal drug prescription and detection of specific drugs that may have an impact on cognitive performance.

Improved de-identification of physician notes through integrative modeling of both public and private medical text

PubMed Central

2013-01-01

Background Physician notes routinely recorded during patient care represent a vast and underutilized resource for human disease studies on a population scale. Their use in research is primarily limited by the need to separate confidential patient information from clinical annotations, a process that is resource-intensive when performed manually. This study seeks to create an automated method for de-identifying physician notes that does not require large amounts of private information: in addition to training a model to recognize Protected Health Information (PHI) within private physician notes, we reverse the problem and train a model to recognize non-PHI words and phrases that appear in public medical texts. Methods Public and private medical text sources were analyzed to distinguish common medical words and phrases from Protected Health Information. Patient identifiers are generally nouns and numbers that appear infrequently in medical literature. To quantify this relationship, term frequencies and part of speech tags were compared between journal publications and physician notes. Standard medical concepts and phrases were then examined across ten medical dictionaries. Lists and rules were included from the US census database and previously published studies. In total, 28 features were used to train decision tree classifiers. Results The model successfully recalled 98% of PHI tokens from 220 discharge summaries. Cost sensitive classification was used to weight recall over precision (98% F10 score, 76% F1 score). More than half of the false negatives were the word “of” appearing in a hospital name. All patient names, phone numbers, and home addresses were at least partially redacted. Medical concepts such as “elevated white blood cell count” were informative for de-identification. The results exceed the previously approved criteria established by four Institutional Review Boards. Conclusions The results indicate that distributional differences between

Improved de-identification of physician notes through integrative modeling of both public and private medical text.

PubMed

McMurry, Andrew J; Fitch, Britt; Savova, Guergana; Kohane, Isaac S; Reis, Ben Y

2013-10-02

Physician notes routinely recorded during patient care represent a vast and underutilized resource for human disease studies on a population scale. Their use in research is primarily limited by the need to separate confidential patient information from clinical annotations, a process that is resource-intensive when performed manually. This study seeks to create an automated method for de-identifying physician notes that does not require large amounts of private information: in addition to training a model to recognize Protected Health Information (PHI) within private physician notes, we reverse the problem and train a model to recognize non-PHI words and phrases that appear in public medical texts. Public and private medical text sources were analyzed to distinguish common medical words and phrases from Protected Health Information. Patient identifiers are generally nouns and numbers that appear infrequently in medical literature. To quantify this relationship, term frequencies and part of speech tags were compared between journal publications and physician notes. Standard medical concepts and phrases were then examined across ten medical dictionaries. Lists and rules were included from the US census database and previously published studies. In total, 28 features were used to train decision tree classifiers. The model successfully recalled 98% of PHI tokens from 220 discharge summaries. Cost sensitive classification was used to weight recall over precision (98% F10 score, 76% F1 score). More than half of the false negatives were the word "of" appearing in a hospital name. All patient names, phone numbers, and home addresses were at least partially redacted. Medical concepts such as "elevated white blood cell count" were informative for de-identification. The results exceed the previously approved criteria established by four Institutional Review Boards. The results indicate that distributional differences between private and public medical text can be used to

Resources for comparing the speed and performance of medical autocoders.

PubMed

Berman, Jules J

2004-06-15

Concept indexing is a popular method for characterizing medical text, and is one of the most important early steps in many data mining efforts. Concept indexing differs from simple word or phrase indexing because concepts are typically represented by a nomenclature code that binds a medical concept to all equivalent representations. A concept search on the term renal cell carcinoma would be expected to find occurrences of hypernephroma, and renal carcinoma (concept equivalents). The purpose of this study is to provide freely available resources to compare speed and performance among different autocoders. These tools consist of: 1) a public domain autocoder written in Perl (a free and open source programming language that installs on any operating system); 2) a nomenclature database derived from the unencumbered subset of the publicly available Unified Medical Language System; 3) a large corpus of autocoded output derived from a publicly available medical text. A simple lexical autocoder was written that parses plain-text into a listing of all 1,2,3, and 4-word strings contained in text, assigning a nomenclature code for text strings that match terms in the nomenclature. The nomenclature used is the unencumbered subset of the 2003 Unified Medical Language System (UMLS). The unencumbered subset of UMLS was reduced to exclude homonymous one-word terms and proper names, resulting in a term/code data dictionary containing about a half million medical terms. The Online Mendelian Inheritance in Man (OMIM), a 92+ Megabyte publicly available medical opus, was used as sample medical text for the autocoder. The autocoding Perl script is remarkably short, consisting of just 38 command lines. The 92+ Megabyte OMIM file was completely autocoded in 869 seconds on a 2.4 GHz processor (less than 10 seconds per Megabyte of text). The autocoded output file (9,540,442 bytes) contains 367,963 coded terms from OMIM and is distributed with this manuscript. A public domain Perl script is

The Association between Charlson Comorbidity Index and the Medical Care Cost of Cancer: A Retrospective Study.

PubMed

Yoon, Seok-Jun; Kim, Eun-Jung; Seo, Hyun-Ju; Oh, In-Hwan

2015-01-01

This study compared comorbidity-related medical care cost associated with different types of cancer, by examining breast (N = 287), colon (N = 272), stomach (N = 614), and lung (N = 391) cancer patients undergoing surgery. Using medical benefits claims data, we calculated Charlson Comorbidity Index (CCI) and total medical cost. The effect of comorbidity on the medical care cost was investigated using multiple regression and logistic regression models and controlling for demographic characteristics and cancer stage. The treatment costs incurred by stomach and colon cancer patients were 1.05- and 1.01-fold higher, respectively, in patients with higher CCI determined. For breast cancer, the highest costs were seen in those with chronic obstructive pulmonary disease (COPD), but the increase in cost reduced as CCI increased. Colon cancer patients with diabetes mellitus and a CCI = 1 score had the highest medical costs. The lowest medical costs were incurred by lung cancer patients with COPD and a CCI = 2 score. The comorbidities had a major impact on the use of medical resources, with chronic comorbidities incurring the highest medical costs. The results indicate that comorbidities affect cancer outcomes and that they must be considered strategies mitigating cancer's economic and social impact.

Medical Image Databases

PubMed Central

Tagare, Hemant D.; Jaffe, C. Carl; Duncan, James

1997-01-01

Abstract Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema. PMID:9147338

Korean association of medical journal editors at the forefront of improving the quality and indexing chances of its member journals.

PubMed

Suh, Chang-Ok; Oh, Se Jeong; Hong, Sung-Tae

2013-05-01

The article overviews some achievements and problems of Korean medical journals published in the highly competitive journal environment. Activities of Korean Association of Medical Journal Editors (KAMJE) are viewed as instrumental for improving the quality of Korean articles, indexing large number of local journals in prestigious bibliographic databases and launching new abstract and citation tracking databases or platforms (eg KoreaMed, KoreaMed Synapse, the Western Pacific Regional Index Medicus [WPRIM]). KAMJE encourages its member journals to upgrade science editing standards and to legitimately increase citation rates, primarily by publishing more great articles with global influence. Experience gained by KAMJE and problems faced by Korean editors may have global implications.

Speeding Up Chemical Searches Using the Inverted Index: the Convergence of Chemoinformatics and Text Search Methods

PubMed Central

Nasr, Ramzi; Vernica, Rares; Li, Chen; Baldi, Pierre

2012-01-01

In ligand-based screening, retrosynthesis, and other chemoinformatics applications, one of-ten seeks to search large databases of molecules in order to retrieve molecules that are similar to a given query. With the expanding size of molecular databases, the efficiency and scalability of data structures and algorithms for chemical searches are becoming increasingly important. Remarkably, both the chemoinformatics and information retrieval communities have converged on similar solutions whereby molecules or documents are represented by binary vectors, or fingerprints, indexing their substructures such as labeled paths for molecules and n-grams for text, with the same Jaccard-Tanimoto similarity measure. As a result, similarity search methods from one field can be adapted to the other. Here we adapt recent, state-of-the-art, inverted index methods from information retrieval to speed up similarity searches in chemoinformatics. Our results show a several-fold speed-up improvement over previous methods for both thresh-old searches and top-K searches. We also provide a mathematical analysis that allows one to predict the level of pruning achieved by the inverted index approach, and validate the quality of these predictions through simulation experiments. All results can be replicated using data freely downloadable from http://cdb.ics.uci.edu/. PMID:22462644

A probabilistic method for computing quantitative risk indexes from medical injuries compensation claims.

PubMed

Dalle Carbonare, S; Folli, F; Patrini, E; Giudici, P; Bellazzi, R

2013-01-01

The increasing demand of health care services and the complexity of health care delivery require Health Care Organizations (HCOs) to approach clinical risk management through proper methods and tools. An important aspect of risk management is to exploit the analysis of medical injuries compensation claims in order to reduce adverse events and, at the same time, to optimize the costs of health insurance policies. This work provides a probabilistic method to estimate the risk level of a HCO by computing quantitative risk indexes from medical injury compensation claims. Our method is based on the estimate of a loss probability distribution from compensation claims data through parametric and non-parametric modeling and Monte Carlo simulations. The loss distribution can be estimated both on the whole dataset and, thanks to the application of a Bayesian hierarchical model, on stratified data. The approach allows to quantitatively assessing the risk structure of the HCO by analyzing the loss distribution and deriving its expected value and percentiles. We applied the proposed method to 206 cases of injuries with compensation requests collected from 1999 to the first semester of 2007 by the HCO of Lodi, in the Northern part of Italy. We computed the risk indexes taking into account the different clinical departments and the different hospitals involved. The approach proved to be useful to understand the HCO risk structure in terms of frequency, severity, expected and unexpected loss related to adverse events.

Understanding and use of phrasal verbs and idioms in medical/nursing texts.

PubMed

Polackova, G

2008-01-01

Phrasal verbs and idioms are frequently used in everyday English. They are also used in more specific language as equivalents for special terms. The use of phrasal verbs and idioms by native patients and health care workers makes their communication easier and less confusing. Non-native medical workers often come across with English phrasal verbs (idioms) in authentic texts and communication. They should be able to recognize them and after analyzing their meaning include them into their own active vocabulary (Ref. 5).

Retrieval of publications addressing shared decision making: an evaluation of full-text searches on medical journal websites.

PubMed

Blanc, Xavier; Collet, Tinh-Hai; Auer, Reto; Iriarte, Pablo; Krause, Jan; Légaré, France; Cornuz, Jacques; Clair, Carole

2015-04-07

Full-text searches of articles increase the recall, defined by the proportion of relevant publications that are retrieved. However, this method is rarely used in medical research due to resource constraints. For the purpose of a systematic review of publications addressing shared decision making, a full-text search method was required to retrieve publications where shared decision making does not appear in the title or abstract. The objective of our study was to assess the efficiency and reliability of full-text searches in major medical journals for identifying shared decision making publications. A full-text search was performed on the websites of 15 high-impact journals in general internal medicine to look up publications of any type from 1996-2011 containing the phrase "shared decision making". The search method was compared with a PubMed search of titles and abstracts only. The full-text search was further validated by requesting all publications from the same time period from the individual journal publishers and searching through the collected dataset. The full-text search for "shared decision making" on journal websites identified 1286 publications in 15 journals compared to 119 through the PubMed search. The search within the publisher-provided publications of 6 journals identified 613 publications compared to 646 with the full-text search on the respective journal websites. The concordance rate was 94.3% between both full-text searches. Full-text searching on medical journal websites is an efficient and reliable way to identify relevant articles in the field of shared decision making for review or other purposes. It may be more widely used in biomedical research in other fields in the future, with the collaboration of publishers and journals toward open-access data.

Measuring motivation for medical treatment: confirming the factor structure of the Achievement Motivation Index for Medical Treatment (AMI-MeT).

PubMed

Hatta, Taichi; Narita, Keiichi; Naria, Keiichi; Yanagihara, Kazuhiro; Ishiguro, Hiroshi; Murayama, Toshinori; Yokode, Masayuki

2016-02-19

Developments in chemotherapy have led to changes in cancer care in Japan, with the government promoting a transition to outpatient chemotherapy. This requires patients and their families to participate more actively in treatment than in the past. However, it remains unclear how patients' motivation for medical treatment affects clinical consultations with their physicians. To investigate this, we developed a psychological index called the Achievement Motive Index for Medical Treatment (AMI-MeT), which comprises self-derived achievement motivation (AMS) and achievement motivation derived from others (AMO). However, its factor structure has not yet been confirmed in populations other than healthy university students. Thus, the aims of this study were to confirm the factor structure of the AMI-MeT in other groups and to determine the convergent and divergent validity of the AMI-MeT. The AMI-MeT was administered to university students (n = 414), apparently healthy workers (n = 154), and cancer patients (n = 51). Multi-group confirmatory factor analysis was conducted and the mean scores of the AMI-MeT were compared between the groups. Correlations between the AMI-MeT and the Self-Construal Scale, comprising independent self-construal (IndSC) and interdependent self-construal (InterSC) subscales, were investigated in another group of students (n = 335). The multi-group confirmatory factor analysis supported a two-factor structure of the AMI-MeT: the weak invariance model was the best fit for the data. The mean scores of the AMI-MeT in apparently healthy workers and cancer patients were significantly higher than that in students (P < .01). The correlation analysis revealed that AMS scores were associated with IndSC scores (r = .25, P < .01) and AMO scores with InterSC scores (r = .30, P < .01). The two-factor model of the AMI-MeT was deemed appropriate for all three groups, and the subscales of the AMI-MeT successfully reflected the

UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

PubMed

Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

2010-08-01

Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications. Published by Elsevier Inc.

MedSynDiKATe--design considerations for an ontology-based medical text understanding system.

PubMed Central

Hahn, U.; Romacker, M.; Schulz, S.

2000-01-01

MedSynDiKATe is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The general system architecture we present integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MedSynDiKATe poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering. PMID:11079899

Computer-Assisted, Programmed Text, and Lecture Modes of Instruction in Three Medical Training Courses: Comparative Evaluation. Final Report.

ERIC Educational Resources Information Center

Deignan, Gerard M.; And Others

This report contains a comparative analysis of the differential effectiveness of computer-assisted instruction (CAI), programmed instructional text (PIT), and lecture methods of instruction in three medical courses--Medical Laboratory, Radiology, and Dental. The summative evaluation includes (1) multiple regression analyses conducted to predict…

Term Familiarity to indicate Perceived and Actual Difficulty of Text in Medical Digital Libraries.

PubMed

Leroy, Gondy; Endicott, James E

2011-10-01

With increasing text digitization, digital libraries can personalize materials for individuals with different education levels and language skills. To this end, documents need meta-information describing their difficulty level. Previous attempts at such labeling used readability formulas but the formulas have not been validated with modern texts and their outcome is seldom associated with actual difficulty. We focus on medical texts and are developing new, evidence-based meta-tags that are associated with perceived and actual text difficulty. This work describes a first tag, term familiarity , which is based on term frequency in the Google corpus. We evaluated its feasibility to serve as a tag by looking at a document corpus (N=1,073) and found that terms in blogs or journal articles displayed unexpected but significantly different scores. Term familiarity was then applied to texts and results from a previous user study (N=86) and could better explain differences for perceived and actual difficulty.

Fibromyalgia and Obesity: The Association Between Body Mass Index and Disability, Depression, History of Abuse, Medications, and Comorbidities.

PubMed

Gota, Carmen E; Kaouk, Sahar; Wilke, William S

2015-09-01

The aim of this study was to determine the frequency of increasing body mass index (BMI) in fibromyalgia (FM) and to understand the impact of increasing BMI on FM. Patients with FM were divided into 3 BMI classifications: normal weight, overweight, and obese. We then sought relationships of increasing BMI to core process FM variables and symptoms and disability, as well as medical comorbidities and demographic, socioeconomic, psychiatric, and treatment data. Of 224 patients, 0.4% were underweight; 25.9%, normal weight; 29.9%, overweight; 43.8%, obese. We found no differences within groups with regard to age, gender, demographics, FM symptoms, FM impact questionnaire scores, and meeting the American College of Rheumatology 1990 criteria and FM survey criteria. Patients with FM who are obese, compared with normal-weight patients, have higher depression scores measured by Patient Health Questionnaire 9 (13.2 [6.6] vs 10.5 [6], P = 0.03), report increased disability by Health Assessment Questionnaire Disability Index scores (1.3 [0.6] vs 0.9 [0.6], P < 0.001), exercise less (8.4% vs 25.4%, P = 0.003), have more medical comorbidities (1.5 [1.3] vs 0.7 [0.9], P < 0.001), take more medications for FM (3.5 [2.2] vs 2.1 [1.8], P < 0.001), and report higher prevalence of abuse (48% vs 33.9%, P = 0.016) and sexual abuse (17.3% vs 6.8%, P = 0.01). Compared with normal-weight patients, obese FM patients are more disabled, report more medical comorbidities, exercise less, have a higher incidence of abuse, report increased depressive symptoms, and take more medications for FM. Bivariate analysis showed association of increasing BMI with the Health Assessment Questionnaire Disability Index (not FM impact questionnaire) and depression. We confirm that the prevalence of overweight and obesity is high in FM and believe that physicians treating FM should be aware of our bivariate linear correlations and discuss weight loss with their FM patients. Even if increasing BMI is not

Extracting and standardizing medication information in clinical text - the MedEx-UIMA system.

PubMed

Jiang, Min; Wu, Yonghui; Shah, Anushi; Priyanka, Priyanka; Denny, Joshua C; Xu, Hua

2014-01-01

Extraction of medication information embedded in clinical text is important for research using electronic health records (EHRs). However, most of current medication information extraction systems identify drug and signature entities without mapping them to standard representation. In this study, we introduced the open source Java implementation of MedEx, an existing high-performance medication information extraction system, based on the Unstructured Information Management Architecture (UIMA) framework. In addition, we developed new encoding modules in the MedEx-UIMA system, which mapped an extracted drug name/dose/form to both generalized and specific RxNorm concepts and translated drug frequency information to ISO standard. We processed 826 documents by both systems and verified that MedEx-UIMA and MedEx (the Python version) performed similarly by comparing both results. Using two manually annotated test sets that contained 300 drug entries from medication list and 300 drug entries from narrative reports, the MedEx-UIMA system achieved F-measures of 98.5% and 97.5% respectively for encoding drug names to corresponding RxNorm generic drug ingredients, and F-measures of 85.4% and 88.1% respectively for mapping drug names/dose/form to the most specific RxNorm concepts. It also achieved an F-measure of 90.4% for normalizing frequency information to ISO standard. The open source MedEx-UIMA system is freely available online at http://code.google.com/p/medex-uima/.

Comparison and combination of several MeSH indexing approaches

PubMed Central

Yepes, Antonio Jose Jimeno; Mork, James G.; Demner-Fushman, Dina; Aronson, Alan R.

2013-01-01

MeSH indexing of MEDLINE is becoming a more difficult task for the group of highly qualified indexing staff at the US National Library of Medicine, due to the large yearly growth of MEDLINE and the increasing size of MeSH. Since 2002, this task has been assisted by the Medical Text Indexer or MTI program. We extend previous machine learning analysis by adding a more diverse set of MeSH headings targeting examples where MTI has been shown to perform poorly. Machine learning algorithms exceed MTI’s performance on MeSH headings that are used very frequently and headings for which the indexing frequency is very low. We find that when we combine the MTI suggestions and the prediction of the learning algorithms, the performance improves compared to any single method for most of the evaluated MeSH headings. PMID:24551371

Comparison and combination of several MeSH indexing approaches.

PubMed

Yepes, Antonio Jose Jimeno; Mork, James G; Demner-Fushman, Dina; Aronson, Alan R

2013-01-01

MeSH indexing of MEDLINE is becoming a more difficult task for the group of highly qualified indexing staff at the US National Library of Medicine, due to the large yearly growth of MEDLINE and the increasing size of MeSH. Since 2002, this task has been assisted by the Medical Text Indexer or MTI program. We extend previous machine learning analysis by adding a more diverse set of MeSH headings targeting examples where MTI has been shown to perform poorly. Machine learning algorithms exceed MTI's performance on MeSH headings that are used very frequently and headings for which the indexing frequency is very low. We find that when we combine the MTI suggestions and the prediction of the learning algorithms, the performance improves compared to any single method for most of the evaluated MeSH headings.

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing

PubMed Central

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. Methods: We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the ‘learning to rank’ framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. Results: DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. Availability and Implementation: The software is available upon request. Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307646

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing.

PubMed

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the 'learning to rank' framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. The software is available upon request. zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Validation of a patient-level medication regimen complexity index as a possible tool to identify patients for medication therapy management intervention.

PubMed

Hirsch, Jan D; Metz, Kelli R; Hosokawa, Patrick W; Libby, Anne M

2014-08-01

The Medication Regimen Complexity Index (MRCI) is a 65-item instrument that can be used to quantify medication regimen complexity at the patient level, capturing all prescribed and over-the-counter medications. Although the MRCI has been used in several studies, the narrow scope of the initial validation limits application at a population or clinical practice level. To conduct a MRCI validation pertinent to the desired clinical use to identify patients for medication therapy management interventions. An expert panel of clinical pharmacists ranked medication regimen complexity for two samples of cases: a single-disease cohort (diabetes mellitus) and a multiple-disease cohort (diabetes mellitus, hypertension, human immunodeficiency virus infection, geriatric depression). Cases for expert panel review were selected from 400 ambulatory clinic patients, and each case description included data that were available via claims or electronic medical records (EMRs). Construct validity was assessed using patient-level MRCI scores, medication count, and additional patient data. Concordance was evaluated using weighted κ agreement statistic, and correlations were determined using Spearman rank-order correlation coefficient (ρ) or Kendall τ. Moderate to good concordance between patient-level MRCI scores and expert medication regimen complexity ranking was observed (claims data, consensus ranking: single-disease cohort 0.55, multiple disease cohort 0.63). In contrast, only fair to moderate concordance was observed for medication count (single-disease cohort 0.33, multiple-disease cohort 0.48). Adding more-detailed administration directions from EMR data did not improve concordance. MRCI convergent validity was supported by strong correlations with medication count (all cohorts 0.90) and moderate correlations with morbidity measures (e.g., all cohorts; number of comorbidities 0.46, Chronic Disease Score 0.46). Nonsignificant correlation of MRCI scores with age and gender

COMPENDEX/TEXT-PAC: RETROSPECTIVE SEARCH.

ERIC Educational Resources Information Center

Standera, Oldrich

The Text-Pac System is capable of generating indexes and bulletins to provide a current information service without the selectivity feature. Indexes of the accumulated data base may also be used as a basis for manual retrospective searching. The manual search involves searching computer-prepared indexes from a machine readable data base produced…

Accuracy of medical subject heading indexing of dental survival analyses.

PubMed

Layton, Danielle M; Clarke, Michael

2014-01-01

To assess the Medical Subject Headings (MeSH) indexing of articles that employed time-to-event analyses to report outcomes of dental treatment in patients. Articles published in 2008 in 50 dental journals with the highest impact factors were hand searched to identify articles reporting dental treatment outcomes over time in human subjects with time-to-event statistics (included, n = 95), without time-to-event statistics (active controls, n = 91), and all other articles (passive controls, n = 6,769). The search was systematic (kappa 0.92 for screening, 0.86 for eligibility). Outcome-, statistic- and time-related MeSH were identified, and differences in allocation between groups were analyzed with chi-square and Fischer exact statistics. The most frequently allocated MeSH for included and active control articles were "dental restoration failure" (77% and 52%, respectively) and "treatment outcome" (54% and 48%, respectively). Outcome MeSH was similar between these groups (86% and 77%, respectively) and significantly greater than passive controls (10%, P < .001). Significantly more statistical MeSH were allocated to the included articles than to the active or passive controls (67%, 15%, and 1%, respectively, P < .001). Sixty-nine included articles specifically used Kaplan-Meier or life table analyses, but only 42% (n = 29) were indexed as such. Significantly more time-related MeSH were allocated to the included than the active controls (92% and 79%, respectively, P = .02), or to the passive controls (22%, P < .001). MeSH allocation within MEDLINE to time-to-event dental articles was inaccurate and inconsistent. Statistical MeSH were omitted from 30% of the included articles and incorrectly allocated to 15% of active controls. Such errors adversely impact search accuracy.

A mortality index for postmarketing surveillance of new medications.

PubMed

Rose, J C; Unis, A S

2000-03-01

The rate of introduction of new pharmaceuticals is growing as a result of advances in molecular pharmacology and targeted drug development. The Fatal Toxicity Index (FTI) has been proposed as a means for monitoring drug toxicity through post-marketing surveillance. The FTI requires data regarding the general availability of a particular agent in the community which, in the US, is proprietary. The authors propose a Mortality Index as an alternative method for calculating relative lethality that does not rely on proprietary information for postmarketing surveillance. Using data from the Toxic Exposure Surveillance System (TESS) a Mortality Index was calculated from the proportion of deaths occurring among all patients who present to a health care facility with an overdose on the same agent or class of agents. The average Mortality Index for various drugs or drug classes for the years 1989 to 1997 is reported. Because the Mortality Index for desipramine appeared much greater than that for the other tricyclics, a chi-squared analysis was performed. The authors conclude, based on this analysis, that desipramine is significantly more likely to lead to death after overdosage than any other tricyclic antidepressant in the study. Also, the Mortality Index appeared to identify the impact of pediatric formulations on overdose lethality. We conclude that the Mortality Index may be a useful tool for determining the safety of agents during the postmarketing surveillance phase.

Quality of pharmacy-specific Medical Subject Headings (MeSH) assignment in pharmacy journals indexed in MEDLINE.

PubMed

Minguet, Fernando; Salgado, Teresa M; van den Boogerd, Lucienne; Fernandez-Llimos, Fernando

2015-01-01

The Medical Subject Headings (MeSH) is the National Library of Medicine (NLM) controlled vocabulary for indexing articles. Inaccuracies in the MeSH thesaurus have been reported for several areas including pharmacy. To assess the quality of pharmacy-specific MeSH assignment to articles indexed in pharmacy journals. The 10 journals containing the highest number of articles published in 2012 indexed under the MeSH 'Pharmacists' were identified. All articles published over a 5-year period (2008-2012) in the 10 previously selected journals were retrieved from PubMed. MeSH terms used to index these articles were extracted and pharmacy-specific MeSH terms were identified. The frequency of use of pharmacy-specific MeSH terms was calculated across journals. A total of 6989 articles were retrieved from the 10 pharmacy journals, of which 328 (4.7%) were articles not fully indexed and therefore did not contain any MeSH terms assigned. Among the 6661 articles fully indexed, the mean number of MeSH terms was 10.1 (SD = 4.0), being 1.0 (SD = 1.3) considered as Major MeSH. Both values significantly varied across journals. The mean number of pharmacy-specific MeSH terms per article was 0.9 (SD = 1.2). A total of 3490 (52.4%) of the 6661 articles were indexed in pharmacy journals without a single pharmacy-specific MeSH. Of the total 67193 MeSH terms assigned to articles, on average 10.5% (SD = 13.9) were pharmacy-specific MeSH. A statistically significant different pattern of pharmacy-specific MeSH assignment was identified across journals (Kruskal-Wallis P < 0.001). The quality of assignment of the existing pharmacy-specific MeSH terms to articles indexed in pharmacy journals can be improved to further enhance evidence gathering in pharmacy. Over half of the articles published in the top-10 journals publishing pharmacy literature were indexed without a single pharmacy-specific MeSH. Copyright © 2015 Elsevier Inc. All rights reserved.

Automation and integration of components for generalized semantic markup of electronic medical texts.

PubMed

Dugan, J M; Berrios, D C; Liu, X; Kim, D K; Kaizer, H; Fagan, L M

1999-01-01

Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models.

Automation and integration of components for generalized semantic markup of electronic medical texts.

PubMed Central

Dugan, J. M.; Berrios, D. C.; Liu, X.; Kim, D. K.; Kaizer, H.; Fagan, L. M.

1999-01-01

Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models. Images Figure 1 Figure 2 Figure 4 Figure 5 PMID:10566457

The relationship of centralization, organizational culture and performance indexes in teaching hospitals affiliated to Tehran University of Medical Sciences.

PubMed

Nasirpour, Amir Ashkan; Gohari, Mahmoud Reza; Moradi, Saied

2010-01-01

One of the main problems in the efficiency and efficacy of an organization is its structural issue. Organizational culture is also considered as an effective factor in the performance of many organizations. The main goal of the present study was to determine the relationship of Centralization and organizational culture and performance indexes in Teaching Hospitals affiliated to Tehran University of Medical Sciences. This correlation study was performed in the year 2007. The population studied consisted of 4408 personnel from 13 hospitals among whom 441 subjects were selected and studied via a class sampling method. Data was compiled using a check list concerning the evaluation status of Centralization and another form concerning performance indexes as well as Robbin's organizational culture questionnaire. Data were obtained from the subjects by self answering and analyzed by using descriptive statistical indexes, T- test and Fisher's exact tests. Among the organizational culture indexes of the hospitals studied, control and organizational identity was better as compared to others (mean=3.32 and 3.30). Concerning the extent of Centralization in the hospitals studied, 53.85 % and 46.15 % were reported to have upper and lower organizational Centralization, respectively. Mean ratio of surgical operations to inpatients was 40%, the mean rate of admissions per active bed was 60.83, mean bed occupancy coefficient was 70.79%, average length of stay was 6.96 days, and mean net death rate was 1.41%. No significant correlation was seen between Centralization degree, organizational culture and performance indexes in teaching hospitals Tehran university of medical sciences. (with 95% confidence interval). Due to the fact that first grade Teaching hospitals use board certified members, expert personnel, and advanced equipments and because of the limitation of patients choice and, the extent of Centralization and many organizational culture components have no significant

Mobile phone text messaging for improving secondary prevention in cardiovascular diseases: A systematic review.

PubMed

Unal, Eda; Giakoumidakis, Konstantinos; Khan, Ehsan; Patelarou, Evridiki

2018-05-23

The aim of this study was to identify, retrieve, critically appraise and synthesize the existing mobile phone text messaging interventions that have been done for secondary prevention of cardiovascular disease (CVD). A systematic review was conducted. The searching was conducted by using the MEDLINE, EMBASE, PsychINFO, CINAHL, PubMed and ScienceDirect databases. Nine randomized controlled trials (RCTs) were eligible and included. The preventive factors measured among studies varied. While the majority of studies examined medication adherence as a main outcome (4), the other 3 studies focused of CVD risk factors combining blood pressure (BP), smoking, body mass index (BMI), physical activity and dietary habits, only 2 studies examined both medication adherence and risk factor modification of CVD. Even though mobile phone text messaging may be beneficial for the secondary prevention of CVD, reliable conclusions on the effects of text messaging cannot be drawn. Copyright © 2018 Elsevier Inc. All rights reserved.

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

PubMed Central

Zweigenbaum, P.; Darmoni, S. J.; Grabar, N.; Douyère, M.; Benichou, J.

2002-01-01

Manually indexed Internet health catalogs such as CliniWeb or CISMeF provide resources for retrieving high-quality health information. Users of these quality-controlled subject gateways are most often referred to them by general search engines such as Google, AltaVista, etc. This raises several questions, among which the following: what is the relative visibility of medical Internet catalogs through search engines? This study addresses this issue by measuring and comparing the visibility of six major, MeSH-indexed health catalogs through four different search engines (AltaVista, Google, Lycos, Northern Light) in two languages (English and French). Over half a million queries were sent to the search engines; for most of these search engines, according to our measures at the time the queries were sent, the most visible catalog for English MeSH terms was CliniWeb and the most visible one for French MeSH terms was CISMeF. PMID:12463965

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

PubMed

Zweigenbaum, P; Darmoni, S J; Grabar, N; Douyère, M; Benichou, J

2002-01-01

Manually indexed Internet health catalogs such as CliniWeb or CISMeF provide resources for retrieving high-quality health information. Users of these quality-controlled subject gateways are most often referred to them by general search engines such as Google, AltaVista, etc. This raises several questions, among which the following: what is the relative visibility of medical Internet catalogs through search engines? This study addresses this issue by measuring and comparing the visibility of six major, MeSH-indexed health catalogs through four different search engines (AltaVista, Google, Lycos, Northern Light) in two languages (English and French). Over half a million queries were sent to the search engines; for most of these search engines, according to our measures at the time the queries were sent, the most visible catalog for English MeSH terms was CliniWeb and the most visible one for French MeSH terms was CISMeF.

Extracting and standardizing medication information in clinical text – the MedEx-UIMA system

PubMed Central

Jiang, Min; Wu, Yonghui; Shah, Anushi; Priyanka, Priyanka; Denny, Joshua C.; Xu, Hua

2014-01-01

Extraction of medication information embedded in clinical text is important for research using electronic health records (EHRs). However, most of current medication information extraction systems identify drug and signature entities without mapping them to standard representation. In this study, we introduced the open source Java implementation of MedEx, an existing high-performance medication information extraction system, based on the Unstructured Information Management Architecture (UIMA) framework. In addition, we developed new encoding modules in the MedEx-UIMA system, which mapped an extracted drug name/dose/form to both generalized and specific RxNorm concepts and translated drug frequency information to ISO standard. We processed 826 documents by both systems and verified that MedEx-UIMA and MedEx (the Python version) performed similarly by comparing both results. Using two manually annotated test sets that contained 300 drug entries from medication list and 300 drug entries from narrative reports, the MedEx-UIMA system achieved F-measures of 98.5% and 97.5% respectively for encoding drug names to corresponding RxNorm generic drug ingredients, and F-measures of 85.4% and 88.1% respectively for mapping drug names/dose/form to the most specific RxNorm concepts. It also achieved an F-measure of 90.4% for normalizing frequency information to ISO standard. The open source MedEx-UIMA system is freely available online at http://code.google.com/p/medex-uima/. PMID:25954575

Representing Medical Knowledge in the Form of Structured Text: The Development of Current Disease Descriptions*

PubMed Central

Nelson, Stuart J.; Sherertz, David D.; Erlbaum, Mark S.; Tuttle, Mark S.

1989-01-01

As part of the Unified Medical Language System (UMLS) initiative, some 900 diseases have been described using “structured text.” Structured text is words and short phrases entered under labelled contexts. Vocabulary is not controlled. The contexts comprise a template for the disease description. The structured text is both manipulable by machine and readable by humans. Use of the template was natural, and only a few problems arose in using the template. Instructions to disease description composers must be explicit in definitions of the contexts. Diseases to be described are chosen, after clustering related diseases, according to the distinctions that physicians practicing in the area under question believe are important. Limiting disease descriptions to primitive observations and to entities otherwise described within the corpus appears to be both feasible and desirable.

Neurolinguistic approach to natural language processing with applications to medical text analysis.

PubMed

Duch, Włodzisław; Matykiewicz, Paweł; Pestian, John

2008-12-01

Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not found directly in the text. The approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications.

Neurolinguistic Approach to Natural Language Processing with Applications to Medical Text Analysis

PubMed Central

Matykiewicz, Paweł; Pestian, John

2008-01-01

Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts that are not found directly in the text. Approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications. PMID:18614334

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years.

PubMed

Wagner, Mathias; Vicinus, Benjamin; Muthra, Sherieda T; Richards, Tereza A; Linder, Roland; Frick, Vilma Oliveira; Groh, Andreas; Rubie, Claudia; Weichert, Frank

2016-06-01

The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining. A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features. The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable. The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Term-Weighting Approaches in Automatic Text Retrieval.

ERIC Educational Resources Information Center

Salton, Gerard; Buckley, Christopher

1988-01-01

Summarizes the experimental evidence that indicates that text indexing systems based on the assignment of appropriately weighted single terms produce retrieval results superior to those obtained with more elaborate text representations, and provides baseline single term indexing models with which more elaborate content analysis procedures can be…

The Nature of Indexing: How Humans and Machines Analyze Messages and Texts for Retrieval. Part II: Machine Indexing, and the Allocation of Human versus Machine Effort.

ERIC Educational Resources Information Center

Anderson, James D.; Perez-Carballo, Jose

2001-01-01

Discussion of human intellectual indexing versus automatic indexing focuses on automatic indexing. Topics include keyword indexing; negative vocabulary control; counting words; comparative counting and weighting; stemming; words versus phrases; clustering; latent semantic indexing; citation indexes; bibliographic coupling; co-citation; relevance…

Text4Heart II - improving medication adherence in people with heart disease: a study protocol for a randomized controlled trial.

PubMed

Maddison, Ralph; Stewart, Ralph; Doughty, Rob; Scott, Tony; Kerr, Andrew; Benatar, Jocelyne; Whittaker, Robyn; Rawstorn, Jonathan C; Rolleston, Anna; Jiang, Yannan; Estabrooks, Paul; Sullivan, Rachel Karen; Bartley, Hannah; Pfaeffli Dale, Leila

2018-01-25

Cardiac rehabilitation (CR) is an essential component of contemporary management for patients with coronary heart disease, including following an acute coronary syndrome (ACS). CR typically involves education and support to assist people following an ACS to make lifestyle changes and prevent subsequent events. Despite its benefits, uptake and participation in tradition CR programs is low. The use of mobile technologies (mHealth) offers the potential to improve reach, access, and delivery of CR support. We aim to determine the effectiveness and cost-effectiveness of a text-messaging intervention (Text4Heart II) to improve adherence to medication and lifestyle change in addition to usual care in people following an ACS. A second aim is to use the RE-AIM framework to inform the potential implementation of Text4Heart II within health services in New Zealand. Text4Heart II is a two-arm, parallel, superiority randomized controlled trial conducted in two large metropolitan hospitals in Auckland, New Zealand. Three hundred and thirty participants will be randomized to either a 24-week theory- and evidence-based personalized text message program to support self-management in addition to usual CR, or usual CR alone (control). Outcomes are assessed at 6 and 12 months. The primary outcome is the proportion of participants adhering to medication at 6 months as measured by dispensed records. Secondary outcomes include medication adherence at 12 months, the proportion of participants adhering to self-reported healthy behaviors (physical activity, fruit and vegetable consumption, moderating alcohol intake and smoking status) measured using a composite health behavior score, self-reported medication adherence, cardiovascular risk factors (lipids, blood pressure), readmissions and related hospital events at 6 and 12 months. A cost-effectiveness analysis will also be conducted. Using the RE-AIM framework, we will determine uptake and sustainability of the intervention. The

She will give birth immediately. Pregnancy and childbirth in medieval Hebrew medical texts produced in the Mediterranean West.

PubMed

Navas, Carmen Caballero

2014-01-01

This essay approaches the medieval Hebrew literature on women's healthcare, with the aim of analysing notions and ideas regarding fertility, pregnancy and childbirth, as conveyed in the texts that form the corpus. Firstly, the work discusses the approach of written texts to pregnancy and childbirth as key elements in the explanation of women's health and the functioning of the female body. In this regard it also explores the role of this approach in the creation of meanings for both the female body and sexual difference. Secondly, it examines female management of pregnancy and childbirth as recorded in Hebrew medical literature. It pays attention to both the attitudes expressed by the authors, translators and copyists regarding female practice, as well as to instances and remedies derived from "local" traditions--that is, from women's experience--in the management of pregnancy and childbirth, also recorded in the texts. Finally, the paper explores how medical theories alien to, or in opposition to, Judaism were adopted or not and, at times, adapted to Jewish notions with the aim of eliminating tensions from the text, on the one hand, and providing Jewish practitioners with adequate training to retain their Christian clientele, on the other.

Text Mining of the Classical Medical Literature for Medicines That Show Potential in Diabetic Nephropathy

PubMed Central

Zhang, Lei; Li, Yin; Guo, Xinfeng; May, Brian H.; Xue, Charlie C. L.; Yang, Lihong; Liu, Xusheng

2014-01-01

Objectives. To apply modern text-mining methods to identify candidate herbs and formulae for the treatment of diabetic nephropathy. Methods. The method we developed includes three steps: (1) identification of candidate ancient terms; (2) systemic search and assessment of medical records written in classical Chinese; (3) preliminary evaluation of the effect and safety of candidates. Results. Ancient terms Xia Xiao, Shen Xiao, and Xiao Shen were determined as the most likely to correspond with diabetic nephropathy and used in text mining. A total of 80 Chinese formulae for treating conditions congruent with diabetic nephropathy recorded in medical books from Tang Dynasty to Qing Dynasty were collected. Sao si tang (also called Reeling Silk Decoction) was chosen to show the process of preliminary evaluation of the candidates. It had promising potential for development as new agent for the treatment of diabetic nephropathy. However, further investigations about the safety to patients with renal insufficiency are still needed. Conclusions. The methods developed in this study offer a targeted approach to identifying traditional herbs and/or formulae as candidates for further investigation in the search for new drugs for modern disease. However, more effort is still required to improve our techniques, especially with regard to compound formulae. PMID:24744808

The impact of tailored text messages on health beliefs and medication adherence in adults with diabetes: A randomized pilot study.

PubMed

Gatwood, Justin; Balkrishnan, Rajesh; Erickson, Steven R; An, Lawrence C; Piette, John D; Farris, Karen B

2016-01-01

Inadequate medication adherence reduces optimal health outcomes and can lead to increased costs, particularly in patients with diabetes. Efforts to improve adherence have resulted in limited effects; approaches leveraging mobile technology have emerged, but their focus has mainly been limited to simple reminder messages. The purpose of this pilot study was to test the effectiveness of tailored text messages focusing on improving medication adherence and health beliefs in adults with diabetes. Adults aged 21-64, with uncontrolled diabetes, and taking at least one anti-diabetic medication were recruited and randomized into 2 study arms: daily tailored text messaging for 90 days or standard care. Comparing baseline and endpoint survey responses, changes in theory-driven health beliefs and attitudes were assessed. The impact on medication adherence was evaluated using pharmacy claims by calculating the percent of days covered (PDC). A total of 75 subjects were consented, and 48 were randomized. Mean PDC at baseline were comparable between cohorts (84.4% and 87.1%, respectively). Declines in adherence were observed in both groups over time but no significant differences were observed between groups or from baseline to the end of the active study period. Unadjusted tests suggested that perceived benefits and competence might have improved in the intervention arm. Tailoring mobile phone text messages is a novel way to address medication nonadherence and health beliefs; further investigation to this combined technique is needed to better understand its impact on behavior change in adults with diabetes. Copyright © 2016 Elsevier Inc. All rights reserved.

Mining knowledge from corpora: an application to retrieval and indexing.

PubMed

Soualmia, Lina F; Dahamna, Badisse; Darmoni, Stéfan

2008-01-01

The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Association rules method is applied to documents. The process is carried out on three major document categories referring to e-health information consumers: health professionals, students and lay people. Association rules evaluation is founded on statistical measures combined with domain knowledge. Association rules represent existing relations between medical concepts (60.62%) and new knowledge (54.21%). Based on observations, 463 expert rules are defined by medical librarians for retrieval and indexing. Association rules bear out existing relations, produce new knowledge and support users and indexers in document retrieval and indexing.

[Systemic candidiasis in medical intensive care unit: analysis of risk factors and the contribution of colonization index].

PubMed

Massou, S; Ahid, S; Azendour, H; Bensghir, M; Mounir, K; Iken, M; Lmimouni, B E; Balkhi, H; Drissi Kamili, N; Haimeur, C

2013-06-01

Description of the epidemiological and clinical characteristics of the patients introducing risk factors of invasive candidiasis. Analysis of risk factors for candidiasis invasive and evaluation of the contribution of colonization index (CI) in the diagnosis of the systematic candidiasis in medical intensive care. Prospective observational study (October 2007 to October 2009). The selected patients present risk factors of system IC candidiasis with an infectious syndrome or clinical signs suggestive of Candida infection and hospitalized more than 48 hours in medical intensive care unit. Pittet's colonization index was calculated at admission and then once a week added to a blood culture. Patients were classified according to level of evidence of Candida infection and the degree of colonization (CI<0.5, CI ≥ 0.5). The study included 100 patients. Mean age of our patients was 55.8 ± 18.2 years with male prevalence. Neurological disease was the most frequent pathology in admission (48%). The most common risk factors were broad-spectrum antibiotics and foreign material. In the various mycology IC specimens, Candida albicans was the most frequent, followed by C. tropicalis, then C. glabrata. The CI was greater than or equal to 0.5 at 53% of the patients, and less than 0.5 in 47% of the cases. Among the patients, 15% developed an invasive candidiasis. In multivariate analysis, the corticosteroid therapy was associated with a high colonisation (IC ≥ 0.5) and neutropenia with a high risk of systemic candidiasis. The positive predictive value of CI was 26%. The negative predictive value was 98%, the sensitivity and specificity was 93% and 48% respectively. CI has the advantage to provide a quantified data of the patient's situation in relation to the colonization. But, it isn't helpful with patients having an invasive candidiasis in medical intensive care unit. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Block selective redaction for minimizing loss during de-identification of burned in text in irreversibly compressed JPEG medical images.

PubMed

Clunie, David A; Gebow, Dan

2015-01-01

Deidentification of medical images requires attention to both header information as well as the pixel data itself, in which burned-in text may be present. If the pixel data to be deidentified is stored in a compressed form, traditionally it is decompressed, identifying text is redacted, and if necessary, pixel data are recompressed. Decompression without recompression may result in images of excessive or intractable size. Recompression with an irreversible scheme is undesirable because it may cause additional loss in the diagnostically relevant regions of the images. The irreversible (lossy) JPEG compression scheme works on small blocks of the image independently, hence, redaction can selectively be confined only to those blocks containing identifying text, leaving all other blocks unchanged. An open source implementation of selective redaction and a demonstration of its applicability to multiframe color ultrasound images is described. The process can be applied either to standalone JPEG images or JPEG bit streams encapsulated in other formats, which in the case of medical images, is usually DICOM.

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text

PubMed Central

Basaruddin, T.

2016-01-01

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug, the lack of labeled dataset sources and external knowledge, and the multiple token representations for a single drug name. Although many approaches have been proposed to overwhelm the task, some problems remained with poor F-score performance (less than 0.75). This paper presents a new treatment in data representation techniques to overcome some of those challenges. We propose three data representation techniques based on the characteristics of word distribution and word similarities as a result of word embedding training. The first technique is evaluated with the standard NN model, that is, MLP. The second technique involves two deep network classifiers, that is, DBN and SAE. The third technique represents the sentence as a sequence that is evaluated with a recurrent NN model, that is, LSTM. In extracting the drug name entities, the third technique gives the best F-score performance compared to the state of the art, with its average F-score being 0.8645. PMID:27843447

Investigating the Relationships among Metacognitive Strategy Training, Willingness to Read English Medical Texts, and Reading Comprehension Ability Using Structural Equation Modeling

ERIC Educational Resources Information Center

Hassanpour, Masoumeh; Ghonsooly, Behzad; Nooghabi, Mehdi Jabbari; Shafiee, Mohammad Naser

2017-01-01

This quasi-experimental study examined the relationship between students' metacognitive awareness and willingness to read English medical texts. So, a model was proposed and tested using structural equation modeling (SEM) with R software. Participants included 98 medical students of two classes. One class was assigned as the control group and the…

Automatic concept extraction from spoken medical reports.

PubMed

Happe, André; Pouliquen, Bruno; Burgun, Anita; Cuggia, Marc; Le Beux, Pierre

2003-07-01

The objective of this project is to investigate methods whereby a combination of speech recognition and automated indexing methods substitute for current transcription and indexing practices. We based our study on existing speech recognition software programs and on NOMINDEX, a tool that extracts MeSH concepts from medical text in natural language and that is mainly based on a French medical lexicon and on the UMLS. For each document, the process consists of three steps: (1) dictation and digital audio recording, (2) speech recognition, (3) automatic indexing. The evaluation consisted of a comparison between the set of concepts extracted by NOMINDEX after the speech recognition phase and the set of keywords manually extracted from the initial document. The method was evaluated on a set of 28 patient discharge summaries extracted from the MENELAS corpus in French, corresponding to in-patients admitted for coronarography. The overall precision was 73% and the overall recall was 90%. Indexing errors were mainly due to word sense ambiguity and abbreviations. A specific issue was the fact that the standard French translation of MeSH terms lacks diacritics. A preliminary evaluation of speech recognition tools showed that the rate of accurate recognition was higher than 98%. Only 3% of the indexing errors were generated by inadequate speech recognition. We discuss several areas to focus on to improve this prototype. However, the very low rate of indexing errors due to speech recognition errors highlights the potential benefits of combining speech recognition techniques and automatic indexing.

MedXN: an open source medication extraction and normalization tool for clinical text

PubMed Central

Sohn, Sunghwan; Clark, Cheryl; Halgrim, Scott R; Murphy, Sean P; Chute, Christopher G; Liu, Hongfang

2014-01-01

Objective We developed the Medication Extraction and Normalization (MedXN) system to extract comprehensive medication information and normalize it to the most appropriate RxNorm concept unique identifier (RxCUI) as specifically as possible. Methods Medication descriptions in clinical notes were decomposed into medication name and attributes, which were separately extracted using RxNorm dictionary lookup and regular expression. Then, each medication name and its attributes were combined together according to RxNorm convention to find the most appropriate RxNorm representation. To do this, we employed serialized hierarchical steps implemented in Apache's Unstructured Information Management Architecture. We also performed synonym expansion, removed false medications, and employed inference rules to improve the medication extraction and normalization performance. Results An evaluation on test data of 397 medication mentions showed F-measures of 0.975 for medication name and over 0.90 for most attributes. The RxCUI assignment produced F-measures of 0.932 for medication name and 0.864 for full medication information. Most false negative RxCUI assignments in full medication information are due to human assumption of missing attributes and medication names in the gold standard. Conclusions The MedXN system (http://sourceforge.net/projects/ohnlp/files/MedXN/) was able to extract comprehensive medication information with high accuracy and demonstrated good normalization capability to RxCUI as long as explicit evidence existed. More sophisticated inference rules might result in further improvements to specific RxCUI assignments for incomplete medication descriptions. PMID:24637954

Publication trends of shared decision making in 15 high impact medical journals: a full-text review with bibliometric analysis

PubMed Central

2014-01-01

Background Shared Decision Making (SDM) is increasingly advocated as a model for medical decision making. However, there is still low use of SDM in clinical practice. High impact factor journals might represent an efficient way for its dissemination. We aimed to identify and characterize publication trends of SDM in 15 high impact medical journals. Methods We selected the 15 general and internal medicine journals with the highest impact factor publishing original articles, letters and editorials. We retrieved publications from 1996 to 2011 through the full-text search function on each journal website and abstracted bibliometric data. We included publications of any type containing the phrase “shared decision making” or five other variants in their abstract or full text. These were referred to as SDM publications. A polynomial Poisson regression model with logarithmic link function was used to assess the evolution across the period of the number of SDM publications according to publication characteristics. Results We identified 1285 SDM publications out of 229,179 publications in 15 journals from 1996 to 2011. The absolute number of SDM publications by journal ranged from 2 to 273 over 16 years. SDM publications increased both in absolute and relative numbers per year, from 46 (0.32% relative to all publications from the 15 journals) in 1996 to 165 (1.17%) in 2011. This growth was exponential (P < 0.01). We found fewer research publications (465, 36.2% of all SDM publications) than non-research publications, which included non-systematic reviews, letters, and editorials. The increase of research publications across time was linear. Full-text search retrieved ten times more SDM publications than a similar PubMed search (1285 vs. 119 respectively). Conclusion This review in full-text showed that SDM publications increased exponentially in major medical journals from 1996 to 2011. This growth might reflect an increased dissemination of the SDM concept to the

[Chinese periodicals indexed in MEDLINE in 2006].

PubMed

Pan, Lian-Jun; Xia, Xin-Yi; Shang, Xue-Jun; Huang, Yu-Feng; Wang, Xiu-Lai

2006-08-01

For the first time, the Chinese Ministry of Science and Technology published an analysis report of Chinese papers indexed in MEDLINE, which indicates that the Chinese government is paying more and more attention to the role of MEDLINE in the evaluation of scientific research. A total of 4 959 journals are listed in the Lists of Journals Indexed in MEDLINE (2006) published by National Library of Medicine, USA (NLM), of which 95 are published in China (including Hong Kong and Taiwan) and 2 another Chinese periodicals are published abroad. To familiarize MEDLINE to more medical researchers and to help them contribute to the journals indexed in MEDLINE, this article lists the top 10 Chinese medical institution whose published papers were indexed in MEDLINE in 2004 along with the Chinese periodicals indexed in MEDLINE in 2006. And the status of MEDLINE in China is briefly analyzed as well.

The Only Safe SMS Texting Is No SMS Texting.

PubMed

Toth, Cheryl; Sacopulos, Michael J

2015-01-01

Many physicians and practice staff use short messaging service (SMS) text messaging to communicate with patients. But SMS text messaging is unencrypted, insecure, and does not meet HIPAA requirements. In addition, the short and abbreviated nature of text messages creates opportunities for misinterpretation, and can negatively impact patient safety and care. Until recently, asking patients to sign a statement that they understand and accept these risks--as well as having policies, device encryption, and cyber insurance in place--would have been enough to mitigate the risk of using SMS text in a medical practice. But new trends and policies have made SMS text messaging unsafe under any circumstance. This article explains these trends and policies, as well as why only secure texting or secure messaging should be used for physician-patient communication.

Scientometric Analysis of Scientific Validity of Medical Archives Regarding Other Medical Journals in Bosnia and Herzegovina

PubMed Central

Masic, Izet; Begic, Edin; Zunic, Lejla

2016-01-01

Introduction: Medical Archives is the oldest medical journal in Bosnia and Herzegovina (B&H) (founded in 1947.). A total of 104 articles were published in Medical Archives during 2015. Analyzing the type of articles, original articles are present in majority during 2015–80.7% (in last seven years, 561 (76%) were original out of 738). In last seven years, 651 (88.2%) articles were from the field of clinical medicine (preclinical disciplines, in the last three years are more represented than in previous years). Collaboration rate in 2015 was 0,92. Articles written in collaboration of five authors (21.1 %) are found to be predominant. From year to year, most often required time for a decision on acceptance or on the revision prior acceptance is between 50 and 60 days (30% of cases in 2015). During 2015, 47.1% of articles were originally from B&H (eleven countries were represented). H index of Medical Archive for 2014 was 12, and does not vary during the last decade. Findings: In 2015 in B&H about twenty-five journals are issued in the field of biomedical and life sciences in general (six are indexed on Medline/PubMed, one is indexed in the Science Citation Index Expanded (SCIE)/Web of Science base). According to GoogleScholar the biggest h5 index has Bosnian Journal of Basic Medical Sciences (BJBMS) and Medical Archives, while the biggest h5 median has BJBMS i Acta Informatica Medica. The highest H-index (13) in B&H has Izet Masic MD, PhD, Enver Zerem MD, PhD and Semir Vranic MD, PhD, while highest g-index (22) has Enver Zerem MD, PhD (analyzed by software package “Publish or Perish”). Conclusion: By comparing the state of medical publishing in B&H with neighboring countries (Croatia, Serbia, Montenegro), we have concluded that B&H is behind Croatia and Serbia by following parameters: Total Documents, Total Cites and H index but in front of Montenegro. PMID:26980926

Scientometric Analysis of Scientific Validity of Medical Archives Regarding Other Medical Journals in Bosnia and Herzegovina.

PubMed

Masic, Izet; Begic, Edin; Zunic, Lejla

2016-02-01

Medical Archives is the oldest medical journal in Bosnia and Herzegovina (B&H) (founded in 1947.). A total of 104 articles were published in Medical Archives during 2015. Analyzing the type of articles, original articles are present in majority during 2015-80.7% (in last seven years, 561 (76%) were original out of 738). In last seven years, 651 (88.2%) articles were from the field of clinical medicine (preclinical disciplines, in the last three years are more represented than in previous years). Collaboration rate in 2015 was 0,92. Articles written in collaboration of five authors (21.1 %) are found to be predominant. From year to year, most often required time for a decision on acceptance or on the revision prior acceptance is between 50 and 60 days (30% of cases in 2015). During 2015, 47.1% of articles were originally from B&H (eleven countries were represented). H index of Medical Archive for 2014 was 12, and does not vary during the last decade. In 2015 in B&H about twenty-five journals are issued in the field of biomedical and life sciences in general (six are indexed on Medline/PubMed, one is indexed in the Science Citation Index Expanded (SCIE)/Web of Science base). According to GoogleScholar the biggest h5 index has Bosnian Journal of Basic Medical Sciences (BJBMS) and Medical Archives, while the biggest h5 median has BJBMS i Acta Informatica Medica. The highest H-index (13) in B&H has Izet Masic MD, PhD, Enver Zerem MD, PhD and Semir Vranic MD, PhD, while highest g-index (22) has Enver Zerem MD, PhD (analyzed by software package "Publish or Perish"). By comparing the state of medical publishing in B&H with neighboring countries (Croatia, Serbia, Montenegro), we have concluded that B&H is behind Croatia and Serbia by following parameters: Total Documents, Total Cites and H index but in front of Montenegro.

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

Establishment of a Quantitative Medical Technology Evaluation System and Indicators within Medical Institutions.

PubMed

Wu, Suo-Wei; Chen, Tong; Pan, Qi; Wei, Liang-Yu; Wang, Qin; Li, Chao; Song, Jing-Chen; Luo, Ji

2018-06-05

The development and application of medical technologies reflect the medical quality and clinical capacity of a hospital. It is also an effective approach in upgrading medical service and core competitiveness among medical institutions. This study aimed to build a quantitative medical technology evaluation system through questionnaire survey within medical institutions to perform an assessment to medical technologies more objectively and accurately, and promote the management of medical quality technologies and ensure the medical safety of various operations among the hospitals. A two-leveled quantitative medical technology evaluation system was built through a two-round questionnaire survey of chosen experts. The Delphi method was applied in identifying the structure of evaluation system and indicators. The judgment of the experts on the indicators was adopted in building the matrix so that the weight coefficient and maximum eigenvalue (λ max), consistency index (CI), and random consistency ratio (CR) could be obtained and collected. The results were verified through consistency tests, and the index weight coefficient of each indicator was conducted and calculated through analytical hierarchy process. Twenty-six experts of different medical fields were involved in the questionnaire survey, 25 of whom successfully responded to the two-round research. Altogether, 4 primary indicators (safety, effectiveness, innovativeness, and benefits), as well as 13 secondary indicators, were included in the evaluation system. The matrix is built to conduct the λ max, CI, and CR of each expert in the survey, and the index weight coefficients of primary indicators were 0.33, 0.28, 0.27, and 0.12, respectively, and the index weight coefficients of secondary indicators were conducted and calculated accordingly. As the two-round questionnaire survey of experts and statistical analysis were performed and credibility of the results was verified through consistency evaluation test, the

Finding European bioethical literature: an evaluation of the leading abstracting and indexing services

PubMed Central

Fangerau, H

2004-01-01

Objectives: In this study the author aimed to provide information for researchers to help them with the selection of suitable databases for finding medical ethics literature. The quantity of medical ethical literature that is indexed in different existing electronic bibliographies was ascertained. Method: Using the international journal index Ulrich's Periodicals Directory, journals on medical ethics were identified. The electronic bibliographies indexing these journals were analysed. In an additional analysis documentalists indexing bioethical literature were asked to name European journals on medical ethics. The bibliographies indexing these journals were examined. Results: Of 290 journals on medical ethics 173 were indexed in at least one bibliography. Current Contents showed the highest coverage with 66 (22.8%) journals indexed followed by MEDLINE (22.1%). By a combined search in the top ten bibliographies with the highest coverage, a maximum coverage of 45.2% of all journals could be reached. All the bibliographies showed a tendency to index more North American than European literature. This result was verified by the supplementary analysis of a sample of continental European journals. Here EMBASE covered the highest number of journals (20.6%) followed by the Russian Academy of Sciences Bibliographies (19.2%). Conclusion: A medical ethics literature search has to be carried out in several databases in order to reach an adequate collection of literature. The databases one wishes to combine should be carefully chosen. There seems to be a regional bias in the most popular databases, favouring North American periodicals compared with European literature on medical ethics. PMID:15173367

Besides Precision & Recall: Exploring Alternative Approaches to Evaluating an Automatic Indexing Tool for MEDLINE

PubMed Central

Névéol, Aurélie; Zeng, Kelly; Bodenreider, Olivier

2006-01-01

Objective This paper explores alternative approaches for the evaluation of an automatic indexing tool for MEDLINE, complementing the traditional precision and recall method. Materials and methods The performance of MTI, the Medical Text Indexer used at NLM to produce MeSH recommendations for biomedical journal articles is evaluated on a random set of MEDLINE citations. The evaluation examines semantic similarity at the term level (indexing terms). In addition, the documents retrieved by queries resulting from MTI index terms for a given document are compared to the PubMed related citations for this document. Results Semantic similarity scores between sets of index terms are higher than the corresponding Dice similarity scores. Overall, 75% of the original documents and 58% of the top ten related citations are retrieved by queries based on the automatic indexing. Conclusions The alternative measures studied in this paper confirm previous findings and may be used to select particular documents from the test set for a more thorough analysis. PMID:17238409

Besides precision & recall: exploring alternative approaches to evaluating an automatic indexing tool for MEDLINE.

PubMed

Neveol, Aurélie; Zeng, Kelly; Bodenreider, Olivier

2006-01-01

This paper explores alternative approaches for the evaluation of an automatic indexing tool for MEDLINE, complementing the traditional precision and recall method. The performance of MTI, the Medical Text Indexer used at NLM to produce MeSH recommendations for biomedical journal articles is evaluated on a random set of MEDLINE citations. The evaluation examines semantic similarity at the term level (indexing terms). In addition, the documents retrieved by queries resulting from MTI index terms for a given document are compared to the PubMed related citations for this document. Semantic similarity scores between sets of index terms are higher than the corresponding Dice similarity scores. Overall, 75% of the original documents and 58% of the top ten related citations are retrieved by queries based on the automatic indexing. The alternative measures studied in this paper confirm previous findings and may be used to select particular documents from the test set for a more thorough analysis.

A pilot study of a heuristic algorithm for novel template identification from VA electronic medical record text.

PubMed

Redd, Andrew M; Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Tran, Le-Thuy; Samore, Matthew H

2017-07-01

Templates in text notes pose challenges for automated information extraction algorithms. We propose a method that identifies novel templates in plain text medical notes. The identification can then be used to either include or exclude templates when processing notes for information extraction. The two-module method is based on the framework of information foraging and addresses the hypothesis that documents containing templates and the templates within those documents can be identified by common features. The first module takes documents from the corpus and groups those with common templates. This is accomplished through a binned word count hierarchical clustering algorithm. The second module extracts the templates. It uses the groupings and performs a longest common subsequence (LCS) algorithm to obtain the constituent parts of the templates. The method was developed and tested on a random document corpus of 750 notes derived from a large database of US Department of Veterans Affairs (VA) electronic medical notes. The grouping module, using hierarchical clustering, identified 23 groups with 3 documents or more, consisting of 120 documents from the 750 documents in our test corpus. Of these, 18 groups had at least one common template that was present in all documents in the group for a positive predictive value of 78%. The LCS extraction module performed with 100% positive predictive value, 94% sensitivity, and 83% negative predictive value. The human review determined that in 4 groups the template covered the entire document, with the remaining 14 groups containing a common section template. Among documents with templates, the number of templates per document ranged from 1 to 14. The mean and median number of templates per group was 5.9 and 5, respectively. The grouping method was successful in finding like documents containing templates. Of the groups of documents containing templates, the LCS module was successful in deciphering text belonging to the template

Improving and Measuring Inpatient Documentation of Medical Care within the MS-DRG System: Education, Monitoring, and Normalized Case Mix Index

PubMed Central

Rosenbaum, Benjamin P.; Lorenz, Robert R.; Luther, Ralph B.; Knowles-Ward, Lisa; Kelly, Dianne L.; Weil, Robert J.

2014-01-01

Documentation of the care delivered to hospitalized patients is a ubiquitous and important aspect of medical care. The majority of references to documentation and coding are based on the Centers for Medicare and Medicaid Services (CMS) Medicare Severity Diagnosis Related Group (MS-DRG) inpatient prospective payment system (IPPS). We educated the members of a clinical care team in a single department (neurosurgery) at our hospital. We measured subsequent documentation improvements in a simple, meaningful, and reproducible fashion. We created a new metric to measure documentation, termed the “normalized case mix index,” that allows comparison of hospitalizations across multiple unrelated MS-DRG groups. Compared to one year earlier, the traditional case mix index, normalized case mix index, severity of illness, and risk of mortality increased one year after the educational intervention. We encourage other organizations to implement and systematically monitor documentation improvement efforts when attempting to determine the accuracy and quality of documentation achieved. PMID:25214820

Improving and measuring inpatient documentation of medical care within the MS-DRG system: education, monitoring, and normalized case mix index.

PubMed

Rosenbaum, Benjamin P; Lorenz, Robert R; Luther, Ralph B; Knowles-Ward, Lisa; Kelly, Dianne L; Weil, Robert J

2014-01-01

Documentation of the care delivered to hospitalized patients is a ubiquitous and important aspect of medical care. The majority of references to documentation and coding are based on the Centers for Medicare and Medicaid Services (CMS) Medicare Severity Diagnosis Related Group (MS-DRG) inpatient prospective payment system (IPPS). We educated the members of a clinical care team in a single department (neurosurgery) at our hospital. We measured subsequent documentation improvements in a simple, meaningful, and reproducible fashion. We created a new metric to measure documentation, termed the "normalized case mix index," that allows comparison of hospitalizations across multiple unrelated MS-DRG groups. Compared to one year earlier, the traditional case mix index, normalized case mix index, severity of illness, and risk of mortality increased one year after the educational intervention. We encourage other organizations to implement and systematically monitor documentation improvement efforts when attempting to determine the accuracy and quality of documentation achieved.

Framing Service, Benefit, and Credibility Through Images and Texts: A Content Analysis of Online Promotional Messages of Korean Medical Tourism Industry.

PubMed

Jun, Jungmi

2016-07-01

This study examines how the Korean medical tourism industry frames its service, benefit, and credibility issues through texts and images of online brochures. The results of content analysis suggest that the Korean medical tourism industry attempts to frame their medical/health services as "excellence in surgeries and cancer care" and "advanced health technology and facilities." However, the use of cost-saving appeals was limited, which can be seen as a strategy to avoid consumers' association of lower cost with lower quality services, and to stress safety and credibility.

Assessing the role of a medication-indication resource in the treatment relation extraction from clinical text

PubMed Central

Bejan, Cosmin Adrian; Wei, Wei-Qi; Denny, Joshua C

2015-01-01

Objective To evaluate the contribution of the MEDication Indication (MEDI) resource and SemRep for identifying treatment relations in clinical text. Materials and methods We first processed clinical documents with SemRep to extract the Unified Medical Language System (UMLS) concepts and the treatment relations between them. Then, we incorporated MEDI into a simple algorithm that identifies treatment relations between two concepts if they match a medication-indication pair in this resource. For a better coverage, we expanded MEDI using ontology relationships from RxNorm and UMLS Metathesaurus. We also developed two ensemble methods, which combined the predictions of SemRep and the MEDI algorithm. We evaluated our selected methods on two datasets, a Vanderbilt corpus of 6864 discharge summaries and the 2010 Informatics for Integrating Biology and the Bedside (i2b2)/Veteran's Affairs (VA) challenge dataset. Results The Vanderbilt dataset included 958 manually annotated treatment relations. A double annotation was performed on 25% of relations with high agreement (Cohen's κ = 0.86). The evaluation consisted of comparing the manual annotated relations with the relations identified by SemRep, the MEDI algorithm, and the two ensemble methods. On the first dataset, the best F1-measure results achieved by the MEDI algorithm and the union of the two resources (78.7 and 80, respectively) were significantly higher than the SemRep results (72.3). On the second dataset, the MEDI algorithm achieved better precision and significantly lower recall values than the best system in the i2b2 challenge. The two systems obtained comparable F1-measure values on the subset of i2b2 relations with both arguments in MEDI. Conclusions Both SemRep and MEDI can be used to extract treatment relations from clinical text. Knowledge-based extraction with MEDI outperformed use of SemRep alone, but superior performance was achieved by integrating both systems. The integration of knowledge

Looking back to move forward: using history, discourse and text in medical education research: AMEE guide no. 73.

PubMed

Kuper, Ayelet; Whitehead, Cynthia; Hodges, Brian David

2013-01-01

As medical education research continues to diversify methodologically and theoretically, medical education researchers have been increasingly willing to challenge taken-for-granted assumptions about the form, content and function of medical education. In this AMEE guide we describe historical, discourse and text analysis approaches that can help researchers and educators question the inevitability of things that are currently seen as 'natural'. Why is such questioning important? By articulating our assumptions and interrogating the 'naturalness' of the status quo, one can then begin to ask why things are the way they are. Researchers can, for example, ask whether the models of medical education organization and delivery that currently seem 'natural' to them have been developed in order to provide the most benefit to students or patients--or whether they have, rather, been developed in ways that provide power to faculty members, medical schools or the medical profession as a whole. An understanding of the interplay of practices and power is a valuable tool for opening up the field to new possibilities for better medical education. The recognition that our current models, rather than being 'natural', were created in particular historical contexts for any number of contingent reasons leads inexorably to the possibility of change. For if our current ways of doing things are not, in fact, inevitable, not only can they be questioned, they can be made better; they can changed in ways that are attentive to whom they benefit, are congruent with our current beliefs about best practice and may lead to the production of better doctors.

H-index in medicine is driven by original research.

PubMed

Nowak, Jan K; Lubarski, Karol; Kowalik, Lukasz M; Walkowiak, Jaroslaw

2018-02-28

To investigate the contribution of selected types of articles to h-indices of medical researchers. We used the Web of Science to export the publication records of various members from 26 scientific medical societies (13 European, 13 North American) associated with 13 medical specialties. Those included were presidents (n=26), heads of randomly chosen committees (n=52), and randomly selected members of those committees (n=52). Publications contributing to h-index were categorized as research articles, reviews, guidelines, meta-analyses, or other published work. Overall, 3259 items authored by 129 scholars were analyzed. The median h-index was 19.5. The median contribution of research articles to h-index was 84.4%. Researchers in the upper h-index tercile (≥28.5) had a larger share of research articles that contributed to h-index in comparison with those in the lower h-index tercile (≤12.5) (median 87.3% [1st-3rd quartile: 80.0%-93.1%] vs 80.0% [50.0%-88.9%], P=0.015). We observed an analogous difference with regard to guidelines (1.1% [0%-3.7%] vs 0% [0%-0%], P=0.007). Original research drives h-indices in medicine. Although guidelines contribute to h-indices in medicine, their influence is low. The specific role of randomized controlled trials in building h-index in medicine remains to be assessed.

Assessing medication adherence in inflammatory bowel diseases. A comparison between a self-administered scale and a pharmacy refill index.

PubMed

de Castro, María Luisa; Sanromán, Luciano; Martín, Alicia; Figueira, Montserrat; Martínez, Noemi; Hernández, Vicent; Del Campo, Victor; Pineda, Juan R; Martínez-Cadilla, Jesús; Pereira, Santos; Rodríguez Prada, José Ignacio

2017-08-01

Medication non-adherence in inflammatory bowel disease (IBD) has a negative impact on disease outcome. Different tools have been proposed to assess non-adherence. We aimed to compare a self-administered scale and a pharmacy refill index as a reliable measure of medication adherence and to determine what factors are related to adherence. Consecutive non-active IBD outpatients were asked to fill in the self-reported Morisky Medication Adherence Scale (MMAS-8) and the Beliefs about Medication Questionnaire (BMQ). Pharmacy refill data were reviewed from the previous three or six months and the medication possession ratio (MPR) was calculated. Non-adherence was defined as MMAS-8 scores < 6 or MPR < 0.8. Two-hundred and three patients were enrolled (60% ulcerative colitis, 40% Crohn's disease); 51% were men, and the mean age was 46.3 (14) years. Seventy-four per cent of patients were on monotherapy and 26% on combination therapy; altogether, 65% received mesalazine, 46% thiopurines and 16% anti-tumor necrosis factor alfa. Non-adherence rate assessed by MPR was 37% and 22.4% by MMAS-8. Receiver operator curve analysis using a MMAS-8 cut-off of six gave an area under the curve of 0.6 (95% CI 0.5-0.7), p = 0.001. This score had an 85% sensitivity and 34% specificity to predict medication non-adherence, with negative and positive predictive values of 57% and 70% respectively. High scores in the BMQ potential for harm of medication were significantly associated with MPR non-adherence (p = 0.01). The accuracy of MMAS-8 to identify medication non-adherence in inactive IBD outpatients in our setting is poor due to a low specificity and a negative predictive value. Psychosocial factors such as beliefs about medication seem to be related to IBD non-adherence.

The medication appropriateness index at 20: where it started, where it has been, and where it may be going.

PubMed

Hanlon, Joseph T; Schmader, Kenneth E

2013-11-01

Potentially inappropriate prescribing for older adults is a major public health concern. While there are multiple measures of potentially inappropriate prescribing, the medication appropriateness index (MAI) is one of the most common implicit approaches published in the scientific literature. The objective of this narrative review is to describe findings regarding the MAI's reliability, comparison of the MAI with other quality measures of potentially inappropriate prescribing, its predictive validity with important health outcomes, and its responsiveness to change within the framework of randomized controlled trials. A search restricted to English-language literature involving humans aged 65+ years from January 1992 to June 2013 was conducted using MEDLINE and EMBASE databases using the search term 'medication appropriateness index'. A manual search of the reference lists from identified articles and the authors' article files, book chapters, and recent reviews was conducted to identify additional articles. A total of 26 articles were identified for inclusion in this narrative review. The main findings were that the MAI has acceptable inter- and intra-rater reliability, it more frequently detects potentially inappropriate prescribing than a commonly used set of explicit criteria, it predicts adverse health outcomes, and it is able to demonstrate the positive impact of interventions to improve this public health problem. We conclude that the MAI may serve as a valuable tool for measuring potentially inappropriate prescribing in older adults.

Text Mining the History of Medicine.

PubMed

Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia

2016-01-01

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while

Text Mining the History of Medicine

PubMed Central

Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia

2016-01-01

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while

Naval Medical Research Institute Summaries of Research 1991

DTIC Science & Technology

1991-01-01

This SUMMARIES OF RESEARCH is composed of citations to publications, an author index , and a subject index from the Naval Medical Research Institute for the Calendar Year 1991.... Medical Research, Bibliography

Extracting information from the text of electronic medical records to improve case detection: a systematic review

PubMed Central

Carroll, John A; Smith, Helen E; Scott, Donia; Cassell, Jackie A

2016-01-01

Background Electronic medical records (EMRs) are revolutionizing health-related research. One key issue for study quality is the accurate identification of patients with the condition of interest. Information in EMRs can be entered as structured codes or unstructured free text. The majority of research studies have used only coded parts of EMRs for case-detection, which may bias findings, miss cases, and reduce study quality. This review examines whether incorporating information from text into case-detection algorithms can improve research quality. Methods A systematic search returned 9659 papers, 67 of which reported on the extraction of information from free text of EMRs with the stated purpose of detecting cases of a named clinical condition. Methods for extracting information from text and the technical accuracy of case-detection algorithms were reviewed. Results Studies mainly used US hospital-based EMRs, and extracted information from text for 41 conditions using keyword searches, rule-based algorithms, and machine learning methods. There was no clear difference in case-detection algorithm accuracy between rule-based and machine learning methods of extraction. Inclusion of information from text resulted in a significant improvement in algorithm sensitivity and area under the receiver operating characteristic in comparison to codes alone (median sensitivity 78% (codes + text) vs 62% (codes), P = .03; median area under the receiver operating characteristic 95% (codes + text) vs 88% (codes), P = .025). Conclusions Text in EMRs is accessible, especially with open source information extraction algorithms, and significantly improves case detection when combined with codes. More harmonization of reporting within EMR studies is needed, particularly standardized reporting of algorithm accuracy metrics like positive predictive value (precision) and sensitivity (recall). PMID:26911811

Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

PubMed

Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

2015-06-06

Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

[Influence of contractual medical association on inpatient service performance].

PubMed

Wu, Zhi-jun; Jian, Wei-yan

2015-06-18

To study the influence of contractual medical association on inpatient service performance. The data came from "Database of Inpatient Record" administered by Department of Medical Insurance. Using diagnosis related groups (DRG) as the tool of risk-adjustment, the third-tier general hospitals and second-tier general hospitals in medical alliance as the intervention group, and the average level of the same grade local hospitals as the control group, the influence of medical alliance on inpatient service performance was evaluated. The difference in difference (DID) method was used for the data analysis. The assessing indicators included the number of DRG group, case mix index (CMI), the total weight, cost efficiency index and time efficiency index. After the establishment of medical association, compared with the average level of the same grade local hospitals, in the third-tier general hospitals of medical alliance, the growth rate of the total weight had declined, and cost efficiency index had increased, while in the second-tier general hospitals of medical alliance, the CMI value had declined, and the cost efficiency index had increased. Contractual medical association played a role of triage patients, and improved the service levels and management efficiency of the second-tier general hospitals.

Pictures and text in instructions for medical devices: effects on recall and actual performance.

PubMed

Kools, Marieke; van de Wiel, Margaretha W J; Ruiter, Robert A C; Kok, Gerjo

2006-12-01

The present study aimed to contribute to the design of effective health education information. Based on cognitive-psychological theory, pictures were expected to improve understanding of two existing textual instructions for using asthma devices (inhaler chamber and peak flow meter). From an analysis of the affordances and constraints of both devices this effect was expected to be stronger with the inhaler chamber than with the peak flow meter. To test this, both instructions were systematically illustrated with seven line-drawings visualizing the actions. In two separate randomized controlled trials with in total 99 participants from the general public, the original text-only versions were compared to the text-picture versions of the same instruction. Dependent variables were participants' recall of the instructions and the quality of their performance with the instruction observed from video-recordings. Conform expectations, the results showed significant positive effects of pictures on recall and performance in both instructions, especially with the inhaler chamber. Thus, pictures may contribute to a better comprehension and use of medical devices that are inherently less clear. Health educators may optimize instruction design by careful analysis of the device with instruction and observational testing with potential users.

Data Compression in Full-Text Retrieval Systems.

ERIC Educational Resources Information Center

Bell, Timothy C.; And Others

1993-01-01

Describes compression methods for components of full-text systems such as text databases on CD-ROM. Topics discussed include storage media; structures for full-text retrieval, including indexes, inverted files, and bitmaps; compression tools; memory requirements during retrieval; and ranking and information retrieval. (Contains 53 references.)…

Image query and indexing for digital x rays

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Thoma, George R.

1998-12-01

The web-based medical information retrieval system (WebMIRS) allows interned access to databases containing 17,000 digitized x-ray spine images and associated text data from National Health and Nutrition Examination Surveys (NHANES). WebMIRS allows SQL query of the text, and viewing of the returned text records and images using a standard browser. We are now working (1) to determine utility of data directly derived from the images in our databases, and (2) to investigate the feasibility of computer-assisted or automated indexing of the images to support image retrieval of images of interest to biomedical researchers in the field of osteoarthritis. To build an initial database based on image data, we are manually segmenting a subset of the vertebrae, using techniques from vertebral morphometry. From this, we will derive and add to the database vertebral features. This image-derived data will enhance the user's data access capability by enabling the creation of combined SQL/image-content queries.

Automatic Classification of Medical Text: The Influence of Publication Form1

PubMed Central

Cole, William G.; Michael, Patricia A.; Stewart, James G.; Blois, Marsden S.

1988-01-01

Previous research has shown that within the domain of medical journal abstracts the statistical distribution of words is neither random nor uniform, but is highly characteristic. Many words are used mainly or solely by one medical specialty or when writing about one particular level of description. Due to this regularity of usage, automatic classification within journal abstracts has proved quite successful. The present research asks two further questions. It investigates whether this statistical regularity and automatic classification success can also be achieved in medical textbook chapters. It then goes on to see whether the statistical distribution found in textbooks is sufficiently similar to that found in abstracts to permit accurate classification of abstracts based solely on previous knowledge of textbooks. 14 textbook chapters and 45 MEDLINE abstracts were submitted to an automatic classification program that had been trained only on chapters drawn from a standard textbook series. Statistical analysis of the properties of abstracts vs. chapters revealed important differences in word use. Automatic classification performance was good for chapters, but poor for abstracts.

A one-way text messaging intervention for obesity.

PubMed

Ahn, Ahleum; Choi, Jaekyung

2016-04-01

Worldwide, there has been a startling increase in the number of people who are obese or overweight. Obesity increases the risk of cardiovascular disease and overall mortality. Mobile phone messaging is an important means of human communication globally. Because the mobile phone can be used anywhere at any time, mobile phone messaging has the potential to manage obesity. We investigated the effectiveness of a one-way text messaging intervention for obesity. Participants' body mass index and waist circumference were measured at the beginning of the programme and again after 12 weeks. The text message group received text messages about exercise, dietary intake, and general information about obesity three times a week, while the control group did not receive any text messages from the study. Of the 80 participants, 25 subjects in the text message group and 29 participants in the control group completed the study. After adjusting for baseline body mass index, the body mass index was significantly lower in the text message group than in the control group (27.9 vs. 28.3; p = 0.02). After adjusting for the baseline waist circumference, the difference of waist circumference between the text message group and control group was not significant (93.4 vs. 94.6; p = 0.13). The one-way text messaging intervention was a simple and effective way to manage obesity. The one-way text messaging intervention may be a useful method for lifestyle modification in obese subjects. © The Author(s) 2015.

Dietary modification, body mass index (BMI), blood pressure (BP) and cardiovascular risk in medical students of a government medical college of Karachi.

PubMed

Raza, Sajjad; Sheikh, Muhammad Adil; Hussain, Muhammad Fawwad Ahmed; Siddiqui, Saad Ebrahim; Muhammad, Rabia; Aziz, Sina; Qamar, Salima; Saleem, Mohammad Azfar; Waki, Nida; Faruqi, Hina; Zia, Aisha

2010-11-01

To determine the prevalence of major risk factors including dietary modification, Body Mass Index (BMI), Blood Pressure (BP) and physical activity in medical students of government teaching hospitals of Karachi. A cross sectional study was conducted on students of Dow Medical College, Karachi, Pakistan through a structured pre-tested questionnaire. Non-probability purposive sampling was used. Smoking, hypertension, family history of cardiovascular disease (CVD), overweight and low physical activity levels are risk factors the presence of which can lead to development of CVD. Prevalence of these risk factors was determined by asking appropriate questions and through measurement of BMI and blood pressure for overweight and hypertension respectively. Awareness of risk factors was determined through knowledge of the effect of various food substances on development of CVD and of adoption of dietary changes keeping in mind the risk of developing CVD. SPSS 16.0 was used for statistical analysis. A total of 132 medical students were included in the study of which 57 (43.2%) and 75 (56.8%) were male and female respectively with mean age of 20.85 +/- 1.21 years. About 15.9% of students had elevated blood pressure i.e. > or = 140/90 mmHg. Twenty eight percent of the total students were found to be underweight and 17.4% were overweight, 5% had some history of CVD, 56.8% had family history of CVD, 9.4% were smokers and 29.5% had high physical activity level. About 87.1% had modified their diet for preventing CVD. Most of the students had adequate knowledge about the cardiovascular risk factors Majority of students were not overweight. A high prevalence of cardiovascular risk factors; family history and elevated blood pressure was present. Awareness in terms of knowledge was satisfactory but implementation in terms of diet modification and adequate physical activity was lacking.

Medication Regimen Complexity Measured by MRCI: A Systematic Review to Identify Health Outcomes.

PubMed

Alves-Conceição, Vanessa; Rocha, Kérilin Stancine Santos; Silva, Fernanda Vilanova Nascimento; Silva, Rafaella Oliveira Santos; Silva, Daniel Tenório da; Lyra-Jr, Divaldo Pereira de

2018-05-01

To perform a systematic review to identify health outcomes related to medication regimen complexity as measured by the Medication Regimen Complexity Index (MRCI) instrument. Cochrane Library, LILACS, PubMed, Scopus, EMBASE, Open Thesis, and Web of Science were searched from January 1, 2004, until April 02, 2018, using the following search terms: outcome assessment, drug therapy, and Medication Regimen Complexity Index and their synonyms in different combinations. Studies that used the MRCI instrument to measure medication regimen complexity and related it to clinical, humanistic, and/or economic outcomes were evaluated. Two reviewers independently carried out the analysis of the titles, abstracts, and complete texts according to the eligibility criteria, performed data extraction, and evaluated study quality. A total of 23 studies met the inclusion criteria; 18 health outcomes related to medication regimen complexity were found. The health outcomes most influenced by medication regimen complexity were hospital readmission, medication adherence, hospitalization, adverse drug events, and emergency sector visit. Only one study related medication regimen complexity with humanistic outcomes, and no study related medication regimen complexity to economic outcomes. Most of the studies were of good methodological quality. Relevance to Patient Care and Clinical Practice: Health care professionals should pay attention to medication regimen complexity of the patients because this may influence health outcomes. This study identified some health outcomes that may be influenced by medication regimen complexity: hospitalization, hospital readmission, and medication adherence were more prevalent, showing a significant association between MRCI increase and these health outcomes.

Increased Hatha yoga experience predicts lower body mass index and reduced medication use in women over 45 years

PubMed Central

Moliver, N; Mika, EM; Chartrand, MS; Burrus, SWM; Haussmann, RE; Khalsa, SBS

2011-01-01

Background: Yoga has been shown to have many short-term health benefits, but little is known about the extent to which these benefits accrue over a long time frame or with frequent practice. Aims: The purpose of this study was to examine the extent to which body mass index (BMI) and medication use in a sample of female yoga practitioners over 45 years varied according to the length and frequency of yoga practice. Materials and Methods: We administered online surveys to 211 female yoga practitioners aged 45 to 80 years. We used regression analyses to evaluate the relationship of extent of yoga experience to both BMI and medication use after accounting for age and lifestyle factors. We also conducted comparisons with 182 matched controls. Results: Participants had practiced yoga for as long as 50 years and for up to 28 hours per week. There were significant inverse relationships between yoga experience and both BMI and medication load. These significant relationships remained after accounting for age and lifestyle factors. When we computed yoga experience in terms of total calendar years, without accounting for hours of practice, significant relationships did not remain. However, there was no obesity in the 49 participants with more than 25 years of yoga practice. Yoga practitioners were less likely than non-practitioners to use medication for metabolic syndrome, mood disorders, inflammation, and pain. Conclusions: A long-term yoga practice was associated with little or no obesity in a non-probability sample of women over 45 years. Relationships showed a dose-response effect, with increased yoga experience predicting lower BMI and reduced medication use. PMID:22022126

MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence.

PubMed

Liu, Ke; Peng, Shengwen; Wu, Junqiu; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2015-06-15

Medical Subject Headings (MeSHs) are used by National Library of Medicine (NLM) to index almost all citations in MEDLINE, which greatly facilitates the applications of biomedical information retrieval and text mining. To reduce the time and financial cost of manual annotation, NLM has developed a software package, Medical Text Indexer (MTI), for assisting MeSH annotation, which uses k-nearest neighbors (KNN), pattern matching and indexing rules. Other types of information, such as prediction by MeSH classifiers (trained separately), can also be used for automatic MeSH annotation. However, existing methods cannot effectively integrate multiple evidence for MeSH annotation. We propose a novel framework, MeSHLabeler, to integrate multiple evidence for accurate MeSH annotation by using 'learning to rank'. Evidence includes numerous predictions from MeSH classifiers, KNN, pattern matching, MTI and the correlation between different MeSH terms, etc. Each MeSH classifier is trained independently, and thus prediction scores from different classifiers are incomparable. To address this issue, we have developed an effective score normalization procedure to improve the prediction accuracy. MeSHLabeler won the first place in Task 2A of 2014 BioASQ challenge, achieving the Micro F-measure of 0.6248 for 9,040 citations provided by the BioASQ challenge. Note that this accuracy is around 9.15% higher than 0.5724, obtained by MTI. The software is available upon request. © The Author 2015. Published by Oxford University Press.

MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence

PubMed Central

Liu, Ke; Peng, Shengwen; Wu, Junqiu; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2015-01-01

Motivation: Medical Subject Headings (MeSHs) are used by National Library of Medicine (NLM) to index almost all citations in MEDLINE, which greatly facilitates the applications of biomedical information retrieval and text mining. To reduce the time and financial cost of manual annotation, NLM has developed a software package, Medical Text Indexer (MTI), for assisting MeSH annotation, which uses k-nearest neighbors (KNN), pattern matching and indexing rules. Other types of information, such as prediction by MeSH classifiers (trained separately), can also be used for automatic MeSH annotation. However, existing methods cannot effectively integrate multiple evidence for MeSH annotation. Methods: We propose a novel framework, MeSHLabeler, to integrate multiple evidence for accurate MeSH annotation by using ‘learning to rank’. Evidence includes numerous predictions from MeSH classifiers, KNN, pattern matching, MTI and the correlation between different MeSH terms, etc. Each MeSH classifier is trained independently, and thus prediction scores from different classifiers are incomparable. To address this issue, we have developed an effective score normalization procedure to improve the prediction accuracy. Results: MeSHLabeler won the first place in Task 2A of 2014 BioASQ challenge, achieving the Micro F-measure of 0.6248 for 9,040 citations provided by the BioASQ challenge. Note that this accuracy is around 9.15% higher than 0.5724, obtained by MTI. Availability and implementation: The software is available upon request. Contact: zhusf@fudan.edu.cn PMID:26072501

Multi-Character Tries for Text Searching.

ERIC Educational Resources Information Center

Cooper, Lorraine K. D.; Tharp, Alan L.

1993-01-01

Introduces the multicharacter trie as an index structure that can improve the time needed for retrieving full-text materials stored on CD-ROMs. The advantages of this structure compared to other structures are described, and experimental results comparing it to the widely used B+ tree and other structures used for full-text retrieval are…

An Experiment Comparing Lexical and Statistical Methods for Extracting MeSH Terms from Clinical Free Text

PubMed Central

Cooper, Gregory F.; Miller, Randolph A.

1998-01-01

Abstract Objective: A primary goal of the University of Pittsburgh's 1990-94 UMLS-sponsored effort was to develop and evaluate PostDoc (a lexical indexing system) and Pindex (a statistical indexing system) comparatively, and then in combination as a hybrid system. Each system takes as input a portion of the free text from a narrative part of a patient's electronic medical record and returns a list of suggested MeSH terms to use in formulating a Medline search that includes concepts in the text. This paper describes the systems and reports an evaluation. The intent is for this evaluation to serve as a step toward the eventual realization of systems that assist healthcare personnel in using the electronic medical record to construct patient-specific searches of Medline. Design: The authors tested the performances of PostDoc, Pindex, and a hybrid system, using text taken from randomly selected clinical records, which were stratified to include six radiology reports, six pathology reports, and six discharge summaries. They identified concepts in the clinical records that might conceivably be used in performing a patient-specific Medline search. Each system was given the free text of each record as an input. The extent to which a system-derived list of MeSH terms captured the relevant concepts in these documents was determined based on blinded assessments by the authors. Results: PostDoc output a mean of approximately 19 MeSH terms per report, which included about 40% of the relevant report concepts. Pindex output a mean of approximately 57 terms per report and captured about 45% of the relevant report concepts. A hybrid system captured approximately 66% of the relevant concepts and output about 71 terms per report. Conclusion: The outputs of PostDoc and Pindex are complementary in capturing MeSH terms from clinical free text. The results suggest possible approaches to reduce the number of terms output while maintaining the percentage of terms captured, including the

BIRAM: a content-based image retrieval framework for medical images

NASA Astrophysics Data System (ADS)

Moreno, Ramon A.; Furuie, Sergio S.

2006-03-01

In the medical field, digital images are becoming more and more important for diagnostics and therapy of the patients. At the same time, the development of new technologies has increased the amount of image data produced in a hospital. This creates a demand for access methods that offer more than text-based queries for retrieval of the information. In this paper is proposed a framework for the retrieval of medical images that allows the use of different algorithms for the search of medical images by similarity. The framework also enables the search for textual information from an associated medical report and DICOM header information. The proposed system can be used for support of clinical decision making and is intended to be integrated with an open source picture, archiving and communication systems (PACS). The BIRAM has the following advantages: (i) Can receive several types of algorithms for image similarity search; (ii) Allows the codification of the report according to a medical dictionary, improving the indexing of the information and retrieval; (iii) The algorithms can be selectively applied to images with the appropriated characteristics, for instance, only in magnetic resonance images. The framework was implemented in Java language using a MS Access 97 database. The proposed framework can still be improved, by the use of regions of interest (ROI), indexing with slim-trees and integration with a PACS Server.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Chemical-text hybrid search engines.

PubMed

Zhou, Yingyao; Zhou, Bin; Jiang, Shumei; King, Frederick J

2010-01-01

As the amount of chemical literature increases, it is critical that researchers be enabled to accurately locate documents related to a particular aspect of a given compound. Existing solutions, based on text and chemical search engines alone, suffer from the inclusion of "false negative" and "false positive" results, and cannot accommodate diverse repertoire of formats currently available for chemical documents. To address these concerns, we developed an approach called Entity-Canonical Keyword Indexing (ECKI), which converts a chemical entity embedded in a data source into its canonical keyword representation prior to being indexed by text search engines. We implemented ECKI using Microsoft Office SharePoint Server Search, and the resultant hybrid search engine not only supported complex mixed chemical and keyword queries but also was applied to both intranet and Internet environments. We envision that the adoption of ECKI will empower researchers to pose more complex search questions that were not readily attainable previously and to obtain answers at much improved speed and accuracy.

Index to Revised Chapter 6 of the Anglo-American Cataloging Rules (North American Text).

ERIC Educational Resources Information Center

Rhee, Eric A., Comp.; Pease, William, Ed.

As an aid for the descriptive cataloging of monographs, this pamphlet provides guidelines for using Chapter 6 of the Anglo-American Cataloging Rules (AACR), which covers this facet of cataloging practice. A table of contents to Chapter 6 is provided, followed by an alphabetical index of the terms and processes involved in descriptive cataloging…

The description of all four cardinal signs of Parkinson's disease in a Hungarian medical text published in 1690.

PubMed

Bereczki, Dániel

2010-05-01

One of the most prevalent neurological disorders is Parkinson's disease (PD), characterized by four cardinal signs: tremor, bradykinesia, rigor and postural instability. Although individual signs of Parkinson's disease - most frequently tremor - have been described since ancient times, the first systematic description of the disease is attributed to James Parkinson in 1817. Here we present evidence that not only individual signs, but the disease itself with all four cardinal signs were described in 1690 by Ferenc Pápai Páriz, in a Hungarian medical text over 120 years before the classical description of James Parkinson. In this article I draw the reader's attention to the descriptive chapter in Pápai's book that was published in Hungarian, which because it is understood by so few people, has resulted in this description of PD being ignored in the medical literature. Copyright 2009 Elsevier Ltd. All rights reserved.

Competency Index. [Health Technology Cluster.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This competency index lists the competencies included in the 62 units of the Tech Prep Competency Profiles within the Health Technologies Cluster. The unit topics are as follows: employability skills; professionalism; teamwork; computer literacy; documentation; infection control and risk management; medical terminology; anatomy, physiology, and…

Machine-Aided Indexing of Technical Literature

ERIC Educational Resources Information Center

Klingbiel, Paul H.

1973-01-01

To index at the Defense Documentation Center (DDC), an automated system must choose single words or phrases rapidly and economically. Automation of DDC's indexing has been machine-aided from its inception. A machine-aided indexing system is described that indexes one million words of text per hour of CPU time. (22 references) (Author/SJ)

Bounds and inequalities relating h-index, g-index, e-index and generalized impact factor: an improvement over existing models.

PubMed

Abbas, Ash Mohammad

2012-01-01

In this paper, we describe some bounds and inequalities relating h-index, g-index, e-index, and generalized impact factor. We derive the bounds and inequalities relating these indexing parameters from their basic definitions and without assuming any continuous model to be followed by any of them. We verify the theorems using citation data for five Price Medalists. We observe that the lower bound for h-index given by Theorem 2, [formula: see text], g ≥ 1, comes out to be more accurate as compared to Schubert-Glanzel relation h is proportional to C(2/3)P(-1/3) for a proportionality constant of 1, where C is the number of citations and P is the number of papers referenced. Also, the values of h-index obtained using Theorem 2 outperform those obtained using Egghe-Liang-Rousseau power law model for the given citation data of Price Medalists. Further, we computed the values of upper bound on g-index given by Theorem 3, g ≤ (h + e), where e denotes the value of e-index. We observe that the upper bound on g-index given by Theorem 3 is reasonably tight for the given citation record of Price Medalists.

Using animated computer-generated text and graphics to depict the risks and benefits of medical treatment.

PubMed

Tait, Alan R; Voepel-Lewis, Terri; Brennan-Martinez, Colleen; McGonegal, Maureen; Levine, Robert

2012-11-01

Conventional print materials for presenting risks and benefits of treatment are often difficult to understand. This study was undertaken to evaluate and compare subjects' understanding and perceptions of risks and benefits presented using animated computerized text and graphics. Adult subjects were randomized to receive identical risk/benefit information regarding taking statins that was presented on an iPad (Apple Corp, Cupertino, Calif) in 1 of 4 different animated formats: text/numbers, pie chart, bar graph, and pictograph. Subjects completed a questionnaire regarding their preferences and perceptions of the message delivery together with their understanding of the information. Health literacy, numeracy, and need for cognition were measured using validated instruments. There were no differences in subject understanding based on the different formats. However, significantly more subjects preferred graphs (82.5%) compared with text (17.5%, P<.001). Specifically, subjects preferred pictographs (32.0%) and bar graphs (31.0%) over pie charts (19.5%) and text (17.5%). Subjects whose preference for message delivery matched their randomly assigned format (preference match) had significantly greater understanding and satisfaction compared with those assigned to something other than their preference. Results showed that computer-animated depictions of risks and benefits offer an effective means to describe medical risk/benefit statistics. That understanding and satisfaction were significantly better when the format matched the individual's preference for message delivery is important and reinforces the value of "tailoring" information to the individual's needs and preferences. Copyright © 2012 Elsevier Inc. All rights reserved.

Benefits and Limitations of Text Messages to Stimulate Higher Learning Among Community Providers: Participants' Views of an mHealth Intervention to Support Continuing Medical Education in Vietnam

PubMed Central

Sabin, Lora L; Larson Williams, Anna; Le, Bao Ngoc; Herman, Augusta R; Viet Nguyen, Ha; Albanese, Rebecca R; Xiong, Wenjun; Shobiye, Hezekiah OA; Halim, Nafisa; Tran, Lien Thi Ngoc; McNabb, Marion; Hoang, Hai; Falconer, Ariel; Nguyen, Tam Thi Thanh; Gill, Christopher J

2017-01-01

Background: A randomized controlled trial was conducted in 2015 to evaluate a mobile continuing medical education (mCME) intervention that provided daily text messages to community-based physicians' assistants (CBPAs) in Thai Nguyen Province, Vietnam. Although the intervention failed to improve medical knowledge over a 6-month period, a companion qualitative study provided insights on the views and experiences of intervention participants. Methods: We conducted focus group discussions (FGDs) and in-depth interviews (IDIs) among participants randomized to receive text messages containing either simple medical facts or quiz questions. Trained interviewers collected data immediately following the conclusion of the trial in December 2015. Using semi-structured question guides, respondents were queried on their views of the intervention, positive and negative, and perceived impacts of the intervention. During analysis, after learning that the intervention had failed to increase knowledge among participants, we also examined reasons for lack of improvement in medical knowledge. All analyses were performed in NVivo using a thematic approach. Results: A total of 70 CBPAs engaged in one of 8 FGDs or an IDI. One-half were men; average age among all respondents was 40 years. Most (81%) practiced in rural settings and most (51%) focused on general medicine. The mean length of work experience was 3 years. All respondents made positive comments about the intervention; convenience, relevance, and quick feedback (quiz format) were praised. Downsides encompassed lack of depth of information, weak interaction, technology challenges, and challenging/irrelevant messages. Respondents described perceived impacts encompassing increased motivation, knowledge, collegial discussions, Internet use to search for more information, and clinical skills. Overall, they expressed a desire for the intervention to continue and recommended expansion to other medical professionals. Overreliance on the

Benefits and Limitations of Text Messages to Stimulate Higher Learning Among Community Providers: Participants' Views of an mHealth Intervention to Support Continuing Medical Education in Vietnam.

PubMed

Sabin, Lora L; Larson Williams, Anna; Le, Bao Ngoc; Herman, Augusta R; Viet Nguyen, Ha; Albanese, Rebecca R; Xiong, Wenjun; Shobiye, Hezekiah Oa; Halim, Nafisa; Tran, Lien Thi Ngoc; McNabb, Marion; Hoang, Hai; Falconer, Ariel; Nguyen, Tam Thi Thanh; Gill, Christopher J

2017-06-27

A randomized controlled trial was conducted in 2015 to evaluate a mobile continuing medical education (mCME) intervention that provided daily text messages to community-based physicians' assistants (CBPAs) in Thai Nguyen Province, Vietnam. Although the intervention failed to improve medical knowledge over a 6-month period, a companion qualitative study provided insights on the views and experiences of intervention participants. We conducted focus group discussions (FGDs) and in-depth interviews (IDIs) among participants randomized to receive text messages containing either simple medical facts or quiz questions. Trained interviewers collected data immediately following the conclusion of the trial in December 2015. Using semi-structured question guides, respondents were queried on their views of the intervention, positive and negative, and perceived impacts of the intervention. During analysis, after learning that the intervention had failed to increase knowledge among participants, we also examined reasons for lack of improvement in medical knowledge. All analyses were performed in NVivo using a thematic approach. A total of 70 CBPAs engaged in one of 8 FGDs or an IDI. One-half were men; average age among all respondents was 40 years. Most (81%) practiced in rural settings and most (51%) focused on general medicine. The mean length of work experience was 3 years. All respondents made positive comments about the intervention; convenience, relevance, and quick feedback (quiz format) were praised. Downsides encompassed lack of depth of information, weak interaction, technology challenges, and challenging/irrelevant messages. Respondents described perceived impacts encompassing increased motivation, knowledge, collegial discussions, Internet use to search for more information, and clinical skills. Overall, they expressed a desire for the intervention to continue and recommended expansion to other medical professionals. Overreliance on the text messages, lack of

[Assessment of research papers in medical university staff evaluation].

PubMed

Zhou, Qing-hui

2012-06-01

Medical university staff evaluation is a substantial branch of education administration for medical university. Output number of research papers as a direct index reflecting the achievements in academic research, plays an important role in academic research evaluation. Another index, influence of the research paper, is an indirect index for academic research evaluation. This paper mainly introduced some commonly used indexes in evaluation of academic research papers currently, and analyzed the applicability and limitation of each index. The author regards that academic research evaluation in education administration, which is mainly based on evaluation of academic research papers, should combine the evaluation of journals where the papers are published with peer review of the papers, and integrate qualitative evaluation with quantitative evaluation, for the purpose of setting up an objective academic research evaluation system for medical university staff.

Machine-aided indexing at NASA

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1994-01-01

This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.

Optimizing Medical Kits for Spaceflight

NASA Technical Reports Server (NTRS)

Keenan, A. B,; Foy, Millennia; Myers, G.

2014-01-01

The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.

Text mining for the biocuration workflow

PubMed Central

Hirschman, Lynette; Burns, Gully A. P. C; Krallinger, Martin; Arighi, Cecilia; Cohen, K. Bretonnel; Valencia, Alfonso; Wu, Cathy H.; Chatr-Aryamontri, Andrew; Dowell, Karen G.; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G.

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on ‘Text Mining for the BioCuration Workflow’ at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community. PMID:22513129

Text mining for the biocuration workflow.

PubMed

Hirschman, Lynette; Burns, Gully A P C; Krallinger, Martin; Arighi, Cecilia; Cohen, K Bretonnel; Valencia, Alfonso; Wu, Cathy H; Chatr-Aryamontri, Andrew; Dowell, Karen G; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on 'Text Mining for the BioCuration Workflow' at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community.

29 CFR Appendix A to Part 825-Index - [Reserved

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 3 2011-07-01 2011-07-01 false [Reserved] A Appendix A to Part 825-Index Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Appendix A to Part 825—Index [Reserved] ...

29 CFR Appendix A to Part 825-Index - [Reserved

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 3 2012-07-01 2012-07-01 false [Reserved] A Appendix A to Part 825-Index Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Appendix A to Part 825—Index [Reserved] ...

29 CFR Appendix A to Part 825-Index - [Reserved

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false [Reserved] A Appendix A to Part 825-Index Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR OTHER LAWS THE FAMILY AND MEDICAL LEAVE ACT OF 1993 Appendix A to Part 825—Index [Reserved] ...

Emergency Victim Care. A Training Manual for Emergency Medical Technicians. Module 14. Appendix I: Communicating with Deaf and Hearing Impaired Patients. Appendix II: Medical Terminology. Appendix III: EMS Organizations. Appendix IV: Legislation (Ohio). Glossary of Terms. Index. Revised.

ERIC Educational Resources Information Center

Ohio State Dept. of Education, Columbus. Div. of Vocational Education.

This training manual for emergency medical technicians, one of 14 modules that comprise the Emergency Victim Care textbook, contains appendixes, a glossary, and an index. The first appendix is an article on communicating with deaf and hearing-impaired patients. Appendix 2, the largest section in this manual, is an introduction to medical…

Citation Analysis of the Korean Journal of Urology From Web of Science, Scopus, Korean Medical Citation Index, KoreaMed Synapse, and Google Scholar.

PubMed

Huh, Sun

2013-04-01

The Korean Journal of Urology began to be published exclusively in English in 2010 and is indexed in PubMed Central/PubMed. This study analyzed a variety of citation indicators of the Korean Journal of Urology before and after 2010 to clarify the present position of the journal among the urology category journals. The impact factor, SCImago Journal Rank (SJR), impact index, Z-impact factor (ZIF, impact factor excluding self-citation), and Hirsch Index (H-index) were referenced or calculated from Web of Science, Scopus, SCImago Journal & Country Ranking, Korean Medical Citation Index (KoMCI), KoreaMed Synapse, and Google Scholar. Both the impact factor and the total citations rose rapidly beginning in 2011. The 2012 impact factor corresponded to the upper 84.9% in the nephrology-urology category, whereas the 2011 SJR was in the upper 58.5%. The ZIF in KoMCI was one fifth of the impact factor because there are only two other urology journals in KoMCI. Up to 2009, more than half of the citations in the Web of Science were from Korean researchers, but from 2010 to 2012, more than 85% of the citations were from international researchers. The H-indexes from Web of Science, Scopus, KoMCI, KoreaMed Synapse, and Google Scholar were 8, 10, 12, 9, and 18, respectively. The strategy of the language change in 2010 was successful from the perspective of citation indicators. The values of the citation indicators will continue to increase rapidly and consistently as the research achievement of authors of the Korean Journal of Urology increases.

Text Messaging to Improve Hypertension Medication Adherence in African Americans From Primary Care and Emergency Department Settings: Results From Two Randomized Feasibility Studies

PubMed Central

Hirzel, Lindsey; Dawood, Rachelle M; Dawood, Katee L; Nichols, Lauren P; Artinian, Nancy T; Schwiebert, Loren; Yarandi, Hossein N; Roberson, Dana N; Plegue, Melissa A; Mango, LynnMarie C; Levy, Phillip D

2017-01-01

Background Hypertension (HTN) is an important problem in the United States, with an estimated 78 million Americans aged 20 years and older suffering from this condition. Health disparities related to HTN are common in the United States, with African Americans suffering from greater prevalence of the condition than whites, as well as greater severity, earlier onset, and more complications. Medication adherence is an important component of HTN management, but adherence is often poor, and simply forgetting to take medications is often cited as a reason. Mobile health (mHealth) strategies have the potential to be a low-cost and effective method for improving medication adherence that also has broad reach. Objective Our goal was to determine the feasibility, acceptability, and preliminary clinical effectiveness of BPMED, an intervention designed to improve medication adherence among African Americans with uncontrolled HTN, through fully automated text messaging support. Methods We conducted two parallel, unblinded randomized controlled pilot trials with African-American patients who had uncontrolled HTN, recruited from primary care and emergency department (ED) settings. In each trial, participants were randomized to receive either usual care or the BPMED intervention for one month. Data were collected in-person at baseline and one-month follow-up, assessing the effect on medication adherence, systolic and diastolic blood pressure (SBP and DBP), medication adherence self-efficacy, and participant satisfaction. Data for both randomized controlled pilot trials were analyzed separately and combined. Results A total of 58 primary care and 65 ED participants were recruited with retention rates of 91% (53/58) and 88% (57/65), respectively. BPMED participants consistently showed numerically greater, yet nonsignificant, improvements in measures of medication adherence (mean change 0.9, SD 2.0 vs mean change 0.5, SD 1.5, P=.26), SBP (mean change –12.6, SD 24.0 vs mean change �

Sandia Text ANaLysis Extensible librarY Server

DOE Office of Scientific and Technical Information (OSTI.GOV)

2006-05-11

This is a server wrapper for STANLEY (Sandia Text ANaLysis Extensible librarY). STANLEY provides capabilities for analyzing, indexing and searching through text. STANLEY Server exposes this capability through a TCP/IP interface allowing third party applications and remote clients to access it.

[Index Copernicus: The Central and Eastern European Journals Ranking System. Why indexing needed in the region?] .

PubMed

Graczynski, M R

2000-09-10

Index Copernicus is ranking system set up by members of the medical community in the Region. There were created five groups of parameters like scientific, editorial and technical quality, circulation and frequency-market stability, which allow for the generation of such a ranking system. The Authors of the Ranking System are aware of the deficiencies of parametrical analysis of science, however they believe the numbers at least set up clear, objective and just rules for all. Index Copernicus could be said the primary objectives of the system for which it has been created for.

Varying levels of difficulty index of skills-test items randomly selected by examinees on the Korean emergency medical technician licensing examination

PubMed Central

2016-01-01

Purpose: The goal of this study was to characterize the difficulty index of the items in the skills test components of the class I and II Korean emergency medical technician licensing examination (KEMTLE), which requires examinees to select items randomly. Methods: The results of 1,309 class I KEMTLE examinations and 1,801 class II KEMTLE examinations in 2013 were subjected to analysis. Items from the basic and advanced skills test sections of the KEMTLE were compared to determine whether some were significantly more difficult than others. Results: In the class I KEMTLE, all 4 of the items on the basic skills test showed significant variation in difficulty index (P<0.01), as well as 4 of the 5 items on the advanced skills test (P<0.05). In the class II KEMTLE, 4 of the 5 items on the basic skills test showed significantly different difficulty index (P<0.01), as well as all 3 of the advanced skills test items (P<0.01). Conclusion: In the skills test components of the class I and II KEMTLE, the procedure in which examinees randomly select questions should be revised to require examinees to respond to a set of fixed items in order to improve the reliability of the national licensing examination. PMID:26883810

Varying levels of difficulty index of skills-test items randomly selected by examinees on the Korean emergency medical technician licensing examination.

PubMed

Koh, Bongyeun; Hong, Sunggi; Kim, Soon-Sim; Hyun, Jin-Sook; Baek, Milye; Moon, Jundong; Kwon, Hayran; Kim, Gyoungyong; Min, Seonggi; Kang, Gu-Hyun

2016-01-01

The goal of this study was to characterize the difficulty index of the items in the skills test components of the class I and II Korean emergency medical technician licensing examination (KEMTLE), which requires examinees to select items randomly. The results of 1,309 class I KEMTLE examinations and 1,801 class II KEMTLE examinations in 2013 were subjected to analysis. Items from the basic and advanced skills test sections of the KEMTLE were compared to determine whether some were significantly more difficult than others. In the class I KEMTLE, all 4 of the items on the basic skills test showed significant variation in difficulty index (P<0.01), as well as 4 of the 5 items on the advanced skills test (P<0.05). In the class II KEMTLE, 4 of the 5 items on the basic skills test showed significantly different difficulty index (P<0.01), as well as all 3 of the advanced skills test items (P<0.01). In the skills test components of the class I and II KEMTLE, the procedure in which examinees randomly select questions should be revised to require examinees to respond to a set of fixed items in order to improve the reliability of the national licensing examination.

A Text-Mining Framework for Supporting Systematic Reviews.

PubMed

Li, Dingcheng; Wang, Zhen; Wang, Liwei; Sohn, Sunghwan; Shen, Feichen; Murad, Mohammad Hassan; Liu, Hongfang

2016-11-01

Systematic reviews (SRs) involve the identification, appraisal, and synthesis of all relevant studies for focused questions in a structured reproducible manner. High-quality SRs follow strict procedures and require significant resources and time. We investigated advanced text-mining approaches to reduce the burden associated with abstract screening in SRs and provide high-level information summary. A text-mining SR supporting framework consisting of three self-defined semantics-based ranking metrics was proposed, including keyword relevance, indexed-term relevance and topic relevance. Keyword relevance is based on the user-defined keyword list used in the search strategy. Indexed-term relevance is derived from indexed vocabulary developed by domain experts used for indexing journal articles and books. Topic relevance is defined as the semantic similarity among retrieved abstracts in terms of topics generated by latent Dirichlet allocation, a Bayesian-based model for discovering topics. We tested the proposed framework using three published SRs addressing a variety of topics (Mass Media Interventions, Rectal Cancer and Influenza Vaccine). The results showed that when 91.8%, 85.7%, and 49.3% of the abstract screening labor was saved, the recalls were as high as 100% for the three cases; respectively. Relevant studies identified manually showed strong topic similarity through topic analysis, which supported the inclusion of topic analysis as relevance metric. It was demonstrated that advanced text mining approaches can significantly reduce the abstract screening labor of SRs and provide an informative summary of relevant studies.

An Analysis of Japanese Medical Periodicals

PubMed Central

Taniguchi, Mayumi

1965-01-01

Medical periodicals published in Japan were studied by analyzing the journals abstracted in Igaku Chuo Zasshi (ICZ), the most comprehensive abstracting service for Japanese medical journal articles. Since the inauguration of medical periodicals in 1869, the number of journals has increased remarkably. In 1963 ICZ abstracted 1,074 journals published in Japan (960 in Japanese and 114 in other languages). Of these 1,074 titles, 855 were on medical sciences, of which 740 were substantive. A subject analysis of the substantive journals in ICZ, as compared to the 124 Japanese journals currently indexed in Index Medicus, was also made. Data were presented relating the number of periodicals to the size of the medical scene in Japan and the United States, and it was pointed out that good control of the literature, by whatever methods, requires a knowledge of the extent of the publications. PMID:14223738

Prevalence of cigarette smoking and khat chewing among Aden university medical students and their relationship to BP and body mass index.

PubMed

Laswar, Al Khader N; Darwish, Hashem

2009-09-01

To evaluate the smoking and khat chewing habits in male Aden University medical students and correlate them with blood pressure (BP), body mass index (BMI), and year of training, we randomly selected 100 students of different levels of training and measured their BP, height, and weight, and evaluated their cigarette smoking and khat chewing habits. The mean age of the whole group was 31.8 years. The mean BMI was 23.24 with a range from 22.6 in the in first year medical students to 24.7 (4.4) in 5 th year medical students (P= 0.127). The mean SBP, DBP, and MBP were 120.35, 70.47 and 87.1 mmHg, respectively, and did not change over the years of training. Preva-lence of smoking increased from 20% to 40% and khat chewing from 35% to 90% over the 5 years of training (P= 0.0003). There was a tendency for positive correlation between age and weight, BMI and frequency of khat chewing, and BMI and MBP. We found high prevalence of smoking and khat chewing among the medical students at Aden University and their prevalence increases with student seniority with no significant changes in BMI, SBP, DBP or MBP. There was a weak positive correlation between BMI with SBP, MBP and frequency of Khat chewing.

Clinical records anonymisation and text extraction (CRATE): an open-source software system.

PubMed

Cardinal, Rudolf N

2017-04-26

Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information. Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent. This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research. Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

Selecting Full-Text Undergraduate Periodicals Databases.

ERIC Educational Resources Information Center

Still, Julie M.; Kassabian, Vibiana

1999-01-01

Examines how libraries and librarians can compare full-text general periodical indices, using ProQuest Direct, Periodical Abstracts (via Ovid), and EBSCOhost as examples. Explores breadth and depth of coverage; manipulation of results (email/download/print); ease of use (searching); and indexing quirks. (AEF)

Mapping the literature of diagnostic medical sonography.

PubMed Central

Walcott, B M

1999-01-01

Diagnostic medical sonography has been evolving as a recognized allied health occupation since the early 1970s, but no bibliometric studies of the literature of the field have been published. This study, part of the Medical Library Association Nursing and Allied Health Resources Section's Project for Mapping the Literature of Allied Health, attempted to identify the core journals in diagnostic medical sonography and determine how well these journals are indexed by MEDLINE, EMBASE/Excerpta Medica, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL). Citation analysis was done using the three journals listed for the field by the Brandon/Hill list. Characteristics of two of these three journals affected the results to the extent that more data should be gathered to reach conclusions about the literature of diagnostic medical sonography as a whole. Results of the analysis do suggest that the literature of echocardiography, which is a special area of diagnostic medical sonography, is indexed much more completely by MEDLINE and EMBASE/Excerpta Medica than by CINAHL. Suggestions are made for librarians making collection development decisions in this area of allied health. PMID:10427429

Natural Language Processing Based Instrument for Classification of Free Text Medical Records

PubMed Central

2016-01-01

According to the Ministry of Labor, Health and Social Affairs of Georgia a new health management system has to be introduced in the nearest future. In this context arises the problem of structuring and classifying documents containing all the history of medical services provided. The present work introduces the instrument for classification of medical records based on the Georgian language. It is the first attempt of such classification of the Georgian language based medical records. On the whole 24.855 examination records have been studied. The documents were classified into three main groups (ultrasonography, endoscopy, and X-ray) and 13 subgroups using two well-known methods: Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results obtained demonstrated that both machine learning methods performed successfully, with a little supremacy of SVM. In the process of classification a “shrink” method, based on features selection, was introduced and applied. At the first stage of classification the results of the “shrink” case were better; however, on the second stage of classification into subclasses 23% of all documents could not be linked to only one definite individual subclass (liver or binary system) due to common features characterizing these subclasses. The overall results of the study were successful. PMID:27668260

How do text-messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit.

PubMed

Hoeppner, Bettina B; Hoeppner, Susanne S; Abroms, Lorien C

2017-04-01

To determine the degree to which the observed benefit of Text2Quit was accounted for by psychosocial mechanisms derived from its quit smoking messaging versus from the use of extra-programmatic smoking cessation treatments and services. Prospective, multiple mediation model of a randomized controlled trial (RCT). United States nation-wide. A total of 409 adult daily smokers participated. Participants were, on average, 35 years of age, predominantly female (68%), white (79%), lacked a college degree (70%), had medium nicotine dependence (average Fagerström Nicotine Dependence Score score of 5.2) and more than half (62%) had made a previous quit attempt. Adult daily smokers browsing the web for smoking cessation support (n = 409; recruited 19 May2011-10 July 2012) were randomized to receive smoking cessation support via Text2Quit versus a smoking cessation material. Mediators (i.e. changes in psychosocial constructs of health behavior change, use of extra-programmatic treatment) were assessed at 1 month using single-item measures and outcome (i.e. self-reported 7-day point prevalence abstinence) at 6-month follow-up. Mediators accounted for 35% of the effect of Text2Quit on smoking cessation. Only psychosocial mechanisms had complete mediational paths, with increases in self-efficacy [b = 0.10 (0.06-0.15)], quitting know-how [b = 0.07 (0.03-0.11)] and the sense that someone cared [b = 0.06 (0.01-0.11)], partially explaining the conferred benefit of Text2Quit. Use of outside resources, including treatments promoted explicitly by Text2Quit, i.e. medication [b = 0.001 (-0.01 to 0.01), quitline [b = -0.002 (-0.01 to 0.04)], treatments and resources not promoted by Text2Quit, i.e. online forums [b = 0.01 (-0.01 to 0.04)] and self-help materials [b = -0.01 (-0.04 to 0.02)], did not have complete mediational paths. An interaction effect existed for medication use that suggested that for participants not using medication, Text2Quit conferred substantial

Text mining for traditional Chinese medical knowledge discovery: a survey.

PubMed

Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

2010-08-01

Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

Citation Analysis of the Korean Journal of Urology From Web of Science, Scopus, Korean Medical Citation Index, KoreaMed Synapse, and Google Scholar

PubMed Central

2013-01-01

The Korean Journal of Urology began to be published exclusively in English in 2010 and is indexed in PubMed Central/PubMed. This study analyzed a variety of citation indicators of the Korean Journal of Urology before and after 2010 to clarify the present position of the journal among the urology category journals. The impact factor, SCImago Journal Rank (SJR), impact index, Z-impact factor (ZIF, impact factor excluding self-citation), and Hirsch Index (H-index) were referenced or calculated from Web of Science, Scopus, SCImago Journal & Country Ranking, Korean Medical Citation Index (KoMCI), KoreaMed Synapse, and Google Scholar. Both the impact factor and the total citations rose rapidly beginning in 2011. The 2012 impact factor corresponded to the upper 84.9% in the nephrology-urology category, whereas the 2011 SJR was in the upper 58.5%. The ZIF in KoMCI was one fifth of the impact factor because there are only two other urology journals in KoMCI. Up to 2009, more than half of the citations in the Web of Science were from Korean researchers, but from 2010 to 2012, more than 85% of the citations were from international researchers. The H-indexes from Web of Science, Scopus, KoMCI, KoreaMed Synapse, and Google Scholar were 8, 10, 12, 9, and 18, respectively. The strategy of the language change in 2010 was successful from the perspective of citation indicators. The values of the citation indicators will continue to increase rapidly and consistently as the research achievement of authors of the Korean Journal of Urology increases. PMID:23614057

Risk of endometrial cancer in relation to medical conditions and medication use.

PubMed

Fortuny, Joan; Sima, Camelia; Bayuga, Sharon; Wilcox, Homer; Pulick, Katherine; Faulkner, Shameka; Zauber, Ann G; Olson, Sara H

2009-05-01

We studied the relation of medical conditions related to obesity and medications used for these conditions with endometrial cancer. We also investigated the association of other medical conditions and medications with risk. This U.S. population-based case-control study included 469 endometrial cancer cases and 467 controls. Information on putative risk factors for endometrial cancer was collected through personal interviews. We asked women about their medical history and medications used for six months or longer and the number of years each medication was taken. Risk was strongly associated with increasing obesity (P for trend < 0.001). Among the conditions related to obesity, and after adjustment for age, body mass index, and other risk factors and conditions, uterine fibroids were independently related to an increased cancer risk [adjusted odds ratio (OR), 1.8; 95% confidence interval (95% CI), 1.2-2.5]. Although hypertension was not significantly related to endometrial cancer after adjustment for age and body mass index, the use of thiazide diuretics was independently associated with increased risk (OR, 1.8; 95% CI, 1.1-3.0). Anemia was associated with decreased risk (OR, 0.6; 95% CI, 0.5-0.9). Use of nonsteroidal anti-inflammatory drugs was related to a decreased risk (OR, 0.7; 95% CI, 0.5-0.97). To our knowledge, the observation about thiazide diuretics is novel and requires confirmation in other studies and populations.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Randomised Trial of Text Messaging on Adherence to Cardiovascular Preventive Treatment (INTERACT Trial)

PubMed Central

Wald, David S.; Bestwick, Jonathan P.; Raiman, Lewis; Brendell, Rebecca; Wald, Nicholas J.

2014-01-01

Background About one third of patients prescribed blood pressure or lipid-lowering drugs for the prevention of coronary heart disease and stroke do not take their medication as prescribed. We conducted a randomized trial to evaluate text messaging as a means of improving adherence to cardiovascular disease preventive treatment. Methods 303 patients taking blood pressure and/or lipid-lowering medications were randomly assigned to being sent text messages (Text group, 151) or not being sent them (No text group, 152). Texts were sent daily for 2 weeks, alternate days for 2 weeks and weekly thereafter for 22 weeks (6 months overall), using an automated computer programme. Patients were asked to respond on whether they had taken their medication, whether the text reminded them to do so if they had forgotten, and if they had not taken their medication to determine if there was a reason for not doing so. At 6 months, use of medication was assessed. Results Two patients were lost to follow-up, providing data on 301 for analysis. In the No text group 38/151 (25%) took less than 80% of the prescribed regimen (ie. stopped medication completely or took it on fewer than 22 of the last 28 days of follow-up) compared to 14/150 patients (9%) in the Text group – an improvement in adherence affecting 16 per 100 patients (95% CI 7 to 24), p<0.001. The texts reminded 98/151 patients (65%) to take medication on at least one occasion and lead to 20/151 (13%) who stopped taking medication because of concern over efficacy or side-effects, resuming treatment. Conclusions In patients taking blood pressure or lipid-lowering treatment for the prevention of cardiovascular disease, text messaging improved medication adherence compared with no text messaging. Trial Registration Controlled-Trials.com ISRCTN74757601 PMID:25479285

Classifying medical relations in clinical text via convolutional neural networks.

PubMed

He, Bin; Guan, Yi; Dai, Rui

2018-05-16

Deep learning research on relation classification has achieved solid performance in the general domain. This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. Copyright © 2018. Published by Elsevier B.V.

Investigation into Text Classification With Kernel Based Schemes

DTIC Science & Technology

2010-03-01

Document Matrix TDMs Term-Document Matrices TMG Text to Matrix Generator TN True Negative TP True Positive VSM Vector Space Model xxii THIS PAGE...are represented as a term-document matrix, common evaluation metrics, and the software package Text to Matrix Generator ( TMG ). The classifier...AND METRICS This chapter introduces the indexing capabilities of the Text to Matrix Generator ( TMG ) Toolbox. Specific attention is placed on the

New generic indexing technology

NASA Technical Reports Server (NTRS)

Freeston, Michael

1996-01-01

There has been no fundamental change in the dynamic indexing methods supporting database systems since the invention of the B-tree twenty-five years ago. And yet the whole classical approach to dynamic database indexing has long since become inappropriate and increasingly inadequate. We are moving rapidly from the conventional one-dimensional world of fixed-structure text and numbers to a multi-dimensional world of variable structures, objects and images, in space and time. But, even before leaving the confines of conventional database indexing, the situation is highly unsatisfactory. In fact, our research has led us to question the basic assumptions of conventional database indexing. We have spent the past ten years studying the properties of multi-dimensional indexing methods, and in this paper we draw the strands of a number of developments together - some quite old, some very new, to show how we now have the basis for a new generic indexing technology for the next generation of database systems.

The Nurses' Well-Being Index and Factors Influencing This Index among Nurses in Central China: A Cross-Sectional Study.

PubMed

Meng, Runtang; Luo, Yi; Liu, Bing; Hu, Ying; Yu, Chuanhua

2015-01-01

A discussion and analysis of factors that contribute to nurses' happiness index can be useful in developing effective interventions to improve nurses' enthusiasm, sense of honor and pride and to improve the efficiency and quality of medical services. In this study, 206 registered nurses at the 2011 annual encounter for 12 Hanchuan hospitals completed a questionnaire survey that covered three aspects of the well-being index and thus served as a comprehensive well-being and general information tool. Based on their index score, the nurses' overall happiness level was moderate. The dimensions of the happiness index are listed in descending order of their contribution to the nurses' comprehensive happiness levels: health concerns, friendly relationships, self-worth, altruism, vitality, positive emotions, personality development, life satisfaction and negative emotions. Four variables (positive emotion, life satisfaction, negative emotions, and friendly relationships) jointly explained 47.80% of the total variance of the happiness index; positive emotions had the greatest impact on the happiness index. Appropriate nursing interventions can improve nurses' happiness index scores, thereby increasing nurses' motivation and promoting the development of their nursing practice.

Index pregnancy versus post-index pregnancy in patients with recurrent pregnancy loss.

PubMed

Greenberg, Tzlil; Tzivian, Liliana; Harlev, Avi; Serjienko, Ruslan; Mazor, Moshe; Bashiri, Asher

2015-01-01

To compare pregnancy outcomes of two consecutive pregnancies in a cohort of women with recurrent pregnancy loss (RPL), in order to determine the long-term prognosis of women with RPL managed in a dedicated RPL clinic. A retrospective cohort study including 262 patients with two or more consecutive pregnancy losses followed by two subsequent pregnancies--index pregnancy (IP) and post-index pregnancy (PIP). All patients were evaluated and treated in the RPL clinic in the Soroka University Medical Center. Comparing IP with PIP, no significant difference in perinatal outcome was observed. The perinatal outcome remained encouraging with approximately 73% birth rate (73.7% versus 72.5%; p=0.83). Only 11% of the women with RPL continued to experience pregnancy losses for two subsequent pregnancies. In a multivariate logistic regression analysis, number of miscarriages pre-Index was the only factor independently associated with birth in the PIP. There is no significant difference between IP and PIP regarding perinatal outcome. Appropriate management in the RPL clinic conferred a significant beneficial effect on long-term pregnancy outcome of a cohort of women with RPL.

The (see text) in the Praecepta: The Medical Fee and its Impact on the Patient.

PubMed

Ecca, Giulia

2016-01-01

The brief collection of deontological guidelines entitled Praecepta is one of the most important literary evidence regarding the fee of the ancient physician. This chapter focuses on three passages from the Praecepta, which offer us a wealth of information on this topic. Some technical terms used in the text, such as the term μiσθápiov, show clearly that the author intends both to provide guidelines for the ideal bedside manners and to defend the repute of the physicians from the widespread charge of greed. In some regards, the author of the Praecepta depicts medicine as a 'liberal' art: the good physician disdains monetary gain as the main goal of his service, and aims to safeguard the social status and reputation of the medical profession. On the other hand, the author of the Praecepta enlightens his readers on the bad behaviour of both charlatan physicians and bad-mannered patients.

Characteristics and publication patterns of theses from a Peruvian medical school.

PubMed

Arriola-Quiroz, Isaias; Curioso, Walter H; Cruz-Encarnacion, Maria; Gayoso, Oscar

2010-06-01

Many medical schools require a student thesis before graduation. Publishing results in a peer-reviewed journal could be an indicator of scientific value and acceptability by the scientific community. The publication pattern of theses published by medical students in Peru is unknown. The aim of this study was to assess the characteristics and publication pattern of theses in biomedical-indexed journals conducted by medical students in a university with the highest research output in Peru. Data from registered theses between 2000 and 2003 were obtained from the university library. Publication of theses in biomedical journals was assessed in 2008 by a search strategy using PubMed, Google Scholar, LILACS, LIPECS and SciELO. Four hundred and eighty-two medical theses were registered between 2000 and 2003; 85 (17.6%) were published in biomedical-indexed journals. Of the published theses, 28 (5.8%) were published in MEDLINE-indexed journals, 55 (11.4%) in SciELO-indexed journals, 61 (12.6%) in LILACS-indexed journals and 68 (14.1%) in LIPECS-indexed journals. Most of the published theses (80%) were in Spanish and published in Peruvian journals; and 17 theses (20%) were published in foreign journals (all of them indexed in MEDLINE). In addition, 37 (43.5%) belong primarily to internal medicine, and 24 (28.2%) belong primarily to infectious diseases. Medical students were first authors in 71 (83.5%) of the articles. In this study, most of the published theses were in Spanish, published in local journals and indexed in LIPECS. The percentage of published theses in biomedical journals at this university is comparable with others coming from developed countries.

Scientific Production of Medical Universities in the West of Iran: a Scientometric Analysis.

PubMed

Rasolabadi, Masoud; Khaledi, Shahnaz; Khayati, Fariba; Kalhor, Marya Maryam; Penjvini, Susan; Gharib, Alireza

2015-08-01

This study aimed to compare scientific production by providing quantitative evaluation of science output in five Western Iranian Medical Universities including Hamedan, Ilam, Kermanshah, Kurdistan and Lorestan University of Medical Sciences using scientometrics indicators based on data indexed in Scopus for period between the years 2010 to 2014. In this scientometric study data were collected using Scopus database. Both searching and analyzing features of Scopus were used to data retrieval and analysis. We used Scientometrics indicators including number of publications, number of citations, nationalization index (NI), Internationalization Index (INI), H-index, average number of citations per paper, and growth index. Five Western Iranian Universities produced over 3011 articles from 2010 to 2014. These articles were cited 7158 times with an average rate of 4.2 citations per article. H- Index of under study universities are varying from 14 to 30. Ilam University of Medical Sciences had the highest international collaboration with an INI of 0.33 compared to Hamedan and Kermanshah universities with INI of 0.20 and 0.16 respectively. The lowest international collaboration belonged to Lorestan University of Medical Sciences (0.07). The highest Growth Index belonged to Kurdistan University of Medical Sciences (69.7). Although scientific production of five Western Iranian Medical Universities was increasing, but this trend was not stable. To achieve better performance it is recommended that five Western Iranian Universities stabilize their budgeting and investment policies in research.

Scientific Production of Medical Universities in the West of Iran: a Scientometric Analysis

PubMed Central

Rasolabadi, Masoud; Khaledi, Shahnaz; Khayati, Fariba; Kalhor, Marya Maryam; Penjvini, Susan; Gharib, Alireza

2015-01-01

Introduction: This study aimed to compare scientific production by providing quantitative evaluation of science output in five Western Iranian Medical Universities including Hamedan, Ilam, Kermanshah, Kurdistan and Lorestan University of Medical Sciences using scientometrics indicators based on data indexed in Scopus for period between the years 2010 to 2014. Methods: In this scientometric study data were collected using Scopus database. Both searching and analyzing features of Scopus were used to data retrieval and analysis. We used Scientometrics indicators including number of publications, number of citations, nationalization index (NI), Internationalization Index (INI), H-index, average number of citations per paper, and growth index. Results: Five Western Iranian Universities produced over 3011 articles from 2010 to 2014. These articles were cited 7158 times with an average rate of 4.2 citations per article. H- Index of under study universities are varying from 14 to 30. Ilam University of Medical Sciences had the highest international collaboration with an INI of 0.33 compared to Hamedan and Kermanshah universities with INI of 0.20 and 0.16 respectively. The lowest international collaboration belonged to Lorestan University of Medical Sciences (0.07). The highest Growth Index belonged to Kurdistan University of Medical Sciences (69.7). Conclusion: Although scientific production of five Western Iranian Medical Universities was increasing, but this trend was not stable. To achieve better performance it is recommended that five Western Iranian Universities stabilize their budgeting and investment policies in research. PMID:26483592

Validation of the Chinese version of the Modified Caregivers Strain Index among Hong Kong caregivers: an initiative of medical social workers.

PubMed

Chan, Wallace Chi Ho; Chan, Christopher L F; Suen, Margaret

2013-11-01

Family caregivers may often experience caregiving stress and burden. To systematically assess this issue, medical social workers may need to use a brief and valid measurement in their practice. In the Hong Kong Chinese context, one additional challenge is to examine whether a measurement developed in the West is valid for Hong Kong Chinese caregivers. Thus, medical social workers in Hong Kong initiated this research study to validate the Chinese version of the Modified Caregiver Strain Index (C-M-CSI). A total of 223 Chinese caregivers of patients with various chronic illnesses were recruited for this validation study. C-M-CSI demonstrated good reliability (Cronbach's alpha coefficient = .91), concurrent validity with the Chinese version of the Caregiver Burden Inventory, and discriminant validity with the Chinese version of the Meaning in Life Questionnaire. Factor analysis yielded a single factor as the original M-CSI, which explained 49 percent of variance. Construct validity was shown by differentiating spousal and nonspousal caregivers, as well as caregivers of patients with and without behavioral problems. C-M-CSI is recommended as a brief and valid measurement that can be used by medical social workers in assessing the caregiving strain of Chinese caregivers of patients in Hong Kong.

Applying conscientiousness index: a tool to explore medical students' professionalism in Indonesia.

PubMed

Jaya, Wolter Prakarsa; Rukmini, Elisabeth

2016-07-14

This study was aimed to describe lecturers' perspective concerning the suitable Conscientiousness Index (CI) components and implementations, as well as to compare the CI scores in year 1-4 student batches. Components were formulated from objective measurements based on interviews with 12 faculty members. The components include: attendance, adherence to rules, evaluative feedback submissions, performance in assignments and clinical skills, assignment submissions, volunteerism, accomplishments, and general misconducts. The scores were collected from year 1-4 pre-clinical medical students (N=144) during the first semester of 2014-2015. Final interviews were conducted with 9 faculty members. Quantitative analysis was performed using Kruskal-Wallis and Mann-Whitney test. Qualitative analysis was performed using content analysis. Using Kruskal-Wallis test, significant difference was found in the CI scores among all years (p=0.000). Post-hoc analysis using Mann-Whitney test showed significant difference in all years except year 1 and 4 (p=0.388). Of the 9 lecturers interviewed during the second interviews, 7 endorsed the importance of CI, while 2 doubted its applicability. Due to the unique characteristics of each block, our system had not been able to conduct a balanced CI evaluation, as compared to the original research. We concluded that the implementation of CI would be highly dependent on the faculty members, with their commitment as the main pre-requisite. We hope to involve academic advisors as CI evaluators and improve our student-centered learning for future assessments. Further study is needed to investigate the longitudinal implementation of CI.

48 CFR 3052.211-70 - Index for specifications.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 7 2010-10-01 2010-10-01 false Index for specifications... CLAUSES Text of Provisions and Clauses 3052.211-70 Index for specifications. As prescribed in (HSAR) 48 CFR 3011.204-70 insert the following clause: Index for Specifications (DEC 2003) If an index or table...

Optimization Routine for Generating Medical Kits for Spaceflight Using the Integrated Medical Model

NASA Technical Reports Server (NTRS)

Graham, Kimberli; Myers, Jerry; Goodenow, Deb

2017-01-01

The Integrated Medical Model (IMM) is a MATLAB model that provides probabilistic assessment of the medical risk associated with human spaceflight missions.Different simulations or profiles can be run in which input conditions regarding both mission characteristics and crew characteristics may vary. For each simulation, the IMM records the total medical events that occur and “treats” each event with resources drawn from import scripts. IMM outputs include Total Medical Events (TME), Crew Health Index (CHI), probability of Evacuation (pEVAC), and probability of Loss of Crew Life (pLOCL).The Crew Health Index is determined by the amount of quality time lost (QTL). Previously, an optimization code was implemented in order to efficiently generate medical kits. The kits were optimized to have the greatest benefit possible, given amass and/or volume constraint. A 6-crew, 14-day lunar mission was chosen for the simulation and run through the IMM for 100,000 trials. A built-in MATLAB solver, mixed-integer linear programming, was used for the optimization routine. Kits were generated in 10% increments ranging from 10%-100% of the benefit constraints. Conditions wheremass alone was minimized, volume alone was minimized, and where mass and volume were minimizedjointly were tested.

Discriminability measures for predicting readability of text on textured backgrounds

NASA Technical Reports Server (NTRS)

Scharff, L. F.; Hill, A. L.; Ahumada, A. J. Jr; Watson, A. B. (Principal Investigator)

2000-01-01

Several discriminability measures were examined for their ability to predict reading search times for three levels of text contrast and a range of backgrounds (plain, a periodic texture, and four spatial-frequency-filtered textures created from the periodic texture). Search times indicate that these background variations only affect readability when the text contrast is low, and that spatial frequency content of the background affects readability. These results were not well predicted by the single variables of text contrast (Spearman rank correlation = -0.64) and background RMS contrast (0.08), but a global masking index and a spatial-frequency-selective masking index led to better predictions (-0.84 and -0.81, respectively). c2000 Optical Society of America.

Machine-aided indexing for NASA STI

NASA Technical Reports Server (NTRS)

Wilson, John

1987-01-01

One of the major components of the NASA/STI processing system is machine-aided indexing (MAI). MAI is a computer process that generates a set of indexing terms selected from NASA's thesaurus, is used for indexing technical reports, is based on text, and is reviewed by indexers. This paper summarizes the MAI objectives and discusses the NASA Lexical Dictionary, subject switching, and phrase matching or natural languages. The benefits of using MAI are mentioned, and MAI production improvement and the future of MAI are briefly addressed.

[Birth of otology illustrated by original texts].

PubMed

Mudry, A

2001-12-01

To be born, to appear, to begin. Though setting the birth of otology in the 19th century may seem a bit pretentious, the texts published at that time are ample proof of the fact. The combined impact of technical, scientific, medical and social factors led to the development of otology as a medical specialty. We discuss these different aspects in this article, illustrating them with extracts from the texts of the era. Once could say that the first half of the 19th century was a period of gestation for otology that was to come into full bloom during the second half of the same century.

The Nurses’ Well-Being Index and Factors Influencing This Index among Nurses in Central China: A Cross-Sectional Study

PubMed Central

Liu, Bing; Hu, Ying; Yu, Chuanhua

2015-01-01

Backgrounds/Objectives A discussion and analysis of factors that contribute to nurses’ happiness index can be useful in developing effective interventions to improve nurses’ enthusiasm, sense of honor and pride and to improve the efficiency and quality of medical services. Methods In this study, 206 registered nurses at the 2011 annual encounter for 12 Hanchuan hospitals completed a questionnaire survey that covered three aspects of the well-being index and thus served as a comprehensive well-being and general information tool. Results Based on their index score, the nurses’ overall happiness level was moderate. The dimensions of the happiness index are listed in descending order of their contribution to the nurses’ comprehensive happiness levels: health concerns, friendly relationships, self-worth, altruism, vitality, positive emotions, personality development, life satisfaction and negative emotions. Four variables (positive emotion, life satisfaction, negative emotions, and friendly relationships) jointly explained 47.80% of the total variance of the happiness index; positive emotions had the greatest impact on the happiness index. Conclusions Appropriate nursing interventions can improve nurses’ happiness index scores, thereby increasing nurses’ motivation and promoting the development of their nursing practice. PMID:26680594

In-Depth Indexing of Monograph Literature for an On-Line Retrieval System: A Pilot Project *

PubMed Central

Egeland, Janet

1972-01-01

One of the unique features of the State University of New York (SUNY) Biomedical Communication Network is the availability of depth-indexed monograph information for on-line retrieval. Approximately 8,000 titles from the Upstate Medical Center Library collection in Syracuse, New York, were indexed in depth, chapter-by-chapter, as to subject content using the control vocabulary Medical Subject Headings. Detailed indexing of monographic conference proceedings was considered of particular importance to the project. This attempt to make monograph literature more readily accessible to medical library patrons is interesting from both a philosophical and a technical point of view. This paper will discuss both of these aspects, giving an overall description of the nature of this innovative project. PMID:4403377

[RadLex - German version: a radiological lexicon for indexing image and report information].

PubMed

Marwede, D; Daumke, P; Marko, K; Lobsien, D; Schulz, S; Kahn, T

2009-01-01

Since 2003 the Radiological Society of North America (RSNA) has been developing a lexicon of standardized radiological terms (RadLex) intended to support the structured reporting of imaging observations and the indexing of teaching cases. The aim of this study was to translate the first version of the lexicon (1 - 2007) into German and to implement a language-independent online term browser. RadLex version 1 - 2007 contains 6303 terms in nine main categories. Two radiologists independently translated the lexicon using medical dictionaries. Terms translated differently were revised and translated by consensus. For the development of an online term browser, a text processing algorithm called morphosemantic indexing was used which splits up words into small semantic units and compares those units to language-specific subword thesauri. In total 6240 of 6303 terms (99 %) were translated. Of those terms 3965 were German, 1893 were Latin, 359 were multilingual, and 23 were English terms that are also used in German and were therefore maintained. The online term browser supports a language-independent term search in RadLex (German/English) and other common medical terminology (e. g., ICD 10). The term browser displays term hierarchies and translations in different frames and the complexity of the result lists can be adapted by the user. RadLex version 1 - 2007 developed by the RSNA is now available in German and can be accessed online through a term browser with an efficient search function. This is an important precondition for the future comparison of national and international indexed radiological examination results and the interoperability between digital teaching resources.

How do physicians become medical experts? A test of three competing theories: distinct domains, independent influence and encapsulation models.

PubMed

Violato, Claudio; Gao, Hong; O'Brien, Mary Claire; Grier, David; Shen, E

2018-05-01

The distinction between basic sciences and clinical knowledge which has led to a theoretical debate on how medical expertise is developed has implications for medical school and lifelong medical education. This longitudinal, population based observational study was conducted to test the fit of three theories-knowledge encapsulation, independent influence, distinct domains-of the development of medical expertise employing structural equation modelling. Data were collected from 548 physicians (292 men-53.3%; 256 women-46.7%; mean age = 24.2 years on admission) who had graduated from medical school 2009-2014. They included (1) Admissions data of undergraduate grade point average and Medical College Admission Test sub-test scores, (2) Course performance data from years 1, 2, and 3 of medical school, and (3) Performance on the NBME exams (i.e., Step 1, Step 2 CK, and Step 3). Statistical fit indices (Goodness of Fit Index-GFI; standardized root mean squared residual-SRMR; root mean squared error of approximation-RSMEA) and comparative fit [Formula: see text] of three theories of cognitive development of medical expertise were used to assess model fit. There is support for the knowledge encapsulation three factor model of clinical competency (GFI = 0.973, SRMR = 0.043, RSMEA = 0.063) which had superior fit indices to both the independent influence and distinct domains theories ([Formula: see text] vs [Formula: see text] [[Formula: see text

Visibility of medical informatics regarding bibliometric indices and databases

PubMed Central

2011-01-01

Background The quantitative study of the publication output (bibliometrics) deeply influences how scientific work is perceived (bibliometric visibility). Recently, new bibliometric indices and databases have been established, which may change the visibility of disciplines, institutions and individuals. This study examines the effects of the new indices on the visibility of Medical Informatics. Methods By objective criteria, three sets of journals are chosen, two representing Medical Informatics and a third addressing Internal Medicine as a benchmark. The availability of index data (index coverage) and the aggregate scores of these corpora are compared for journal-related (Journal impact factor, Eigenfactor metrics, SCImago journal rank) and author-related indices (Hirsch-index, Egghes G-index). Correlation analysis compares the dependence of author-related indices. Results The bibliometric visibility depended on the research focus and the citation database: Scopus covers more journals relevant for Medical Informatics than ISI/Thomson Reuters. Journals focused on Medical Informatics' methodology were negatively affected by the Eigenfactor metrics, while the visibility profited from an interdisciplinary research focus. The correlation between Hirsch-indices computed on citation databases and the Internet was strong. Conclusions The visibility of smaller technology-oriented disciplines like Medical Informatics is changed by the new bibliometric indices and databases possibly leading to suitably changed publication strategies. Freely accessible author-related indices enable an easy and adequate individual assessment. PMID:21496230

Mobile Assessment and Treatment for Schizophrenia (MATS): A Pilot Trial of An Interactive Text-Messaging Intervention for Medication Adherence, Socialization, and Auditory Hallucinations

PubMed Central

Granholm, Eric; Ben-Zeev, Dror; Bradshaw, Kristen R.; Holden, Jason L.

2012-01-01

Mobile Assessment and Treatment for Schizophrenia (MATS) employs ambulatory monitoring methods and cognitive behavioral therapy interventions to assess and improve outcomes in consumers with schizophrenia through mobile phone text messaging. Three MATS interventions were developed to target medication adherence, socialization, and auditory hallucinations. Participants received up to 840 text messages over a 12-week intervention period. Fifty-five consumers with schizophrenia or schizoaffective disorder were enrolled, but 13 consumers with more severe negative symptoms, lower functioning, and lower premorbid IQ did not complete the intervention, despite repeated prompting and training. For completers, the average valid response rate for 216 outcome assessment questions over the 12-week period was 86%, and 86% of phones were returned undamaged. Medication adherence improved significantly, but only for individuals who were living independently. Number of social interactions increased significantly and a significant reduction in severity of hallucinations was found. In addition, the probability of endorsing attitudes that could interfere with improvement in these outcomes was also significantly reduced in MATS. Lab-based assessments of more general symptoms and functioning did not change significantly. This pilot study demonstrated that low-intensity text-messaging interventions like MATS are feasible and effective interventions to improve several important outcomes, especially for higher functioning consumers with schizophrenia. PMID:22080492

Comparison of Grouping Methods for Template Extraction from VA Medical Record Text.

PubMed

Redd, Andrew M; Gundlapalli, Adi V; Divita, Guy; Tran, Le-Thuy; Pettey, Warren B P; Samore, Matthew H

2017-01-01

We investigate options for grouping templates for the purpose of template identification and extraction from electronic medical records. We sampled a corpus of 1000 documents originating from Veterans Health Administration (VA) electronic medical record. We grouped documents through hashing and binning tokens (Hashed) as well as by the top 5% of tokens identified as important through the term frequency inverse document frequency metric (TF-IDF). We then compared the approaches on the number of groups with 3 or more and the resulting longest common subsequences (LCSs) common to all documents in the group. We found that the Hashed method had a higher success rate for finding LCSs, and longer LCSs than the TF-IDF method, however the TF-IDF approach found more groups than the Hashed and subsequently more long sequences, however the average length of LCSs were lower. In conclusion, each algorithm appears to have areas where it appears to be superior.

Indexing Anatomical Phrases in Neuro-Radiology Reports to the UMLS 2005AA

PubMed Central

Bashyam, Vijayaraghavan; Taira, Ricky K.

2005-01-01

This work describes a methodology to index anatomical phrases to the 2005AA release of the Unified Medical Language System (UMLS). A phrase chunking tool based on Natural Language Processing (NLP) was developed to identify semantically coherent phrases within medical reports. Using this phrase chunker, a set of 2,551 unique anatomical phrases was extracted from brain radiology reports. These phrases were mapped to the 2005AA release of the UMLS using a vector space model. Precision for the task of indexing unique phrases was 0.87. PMID:16778995

The systematic assessment of traditional evidence from the premodern Chinese medical literature: a text-mining approach.

PubMed

May, Brian H; Zhang, Anthony; Lu, Yubo; Lu, Chuanjian; Xue, Charlie C L

2014-12-01

This project aimed to develop an approach to evaluating information contained in the premodern Traditional Chinese Medicine (TCM) literature that was (1) comprehensive, systematic, and replicable and (2) able to produce quantifiable output that could be used to answer specific research questions in order to identify natural products for clinical and experimental research. The project involved two stages. In stage 1, 14 TCM collections and compendia were evaluated for suitability as sources for searching; 8 of these were compared in detail. The results were published in the Journal of Alternative and Complementary Medicine. Stage 2 developed a text-mining approach for two of these sources. The text-mining approach was developed for Zhong Hua Yi Dian; Encyclopaedia of Traditional Chinese Medicine, 4th edition) and Zhong Yi Fang Ji Da Ci Dian; Great Compendium of Chinese Medical Formulae). This approach developed procedures for search term selection; methods for screening, classifying, and scoring data; procedures for systematic searching and data extraction; data checking procedures; and approaches for analyzing results. Examples are provided for studies of memory impairment and diabetic nephropathy, and issues relating to data interpretation are discussed. This approach to the analysis of large collections of the premodern TCM literature uses widely available sources and provides a text-mining approach that is systematic, replicable, and adaptable to the requirements of the particular project. Researchers can use these methods to explore changes in the names and conceptions of a disease over time, to identify which therapeutic methods have been more or less frequently used in different eras for particular disorders, and to assist in the selection of natural products for research efforts.

Text Readability and Intuitive Simplification: A Comparison of Readability Formulas

ERIC Educational Resources Information Center

Crossley, Scott A.; Allen, David B.; McNamara, Danielle S.

2011-01-01

Texts are routinely simplified for language learners with authors relying on a variety of approaches and materials to assist them in making the texts more comprehensible. Readability measures are one such tool that authors can use when evaluating text comprehensibility. This study compares the Coh-Metrix Second Language (L2) Reading Index, a…

Design and rationale of the Cardiovascular Health and Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study: two randomised controlled trials of text messaging to improve secondary prevention for coronary heart disease and diabetes.

PubMed

Huo, Xiqian; Spatz, Erica S; Ding, Qinglan; Horak, Paul; Zheng, Xin; Masters, Claire; Zhang, Haibo; Irwin, Melinda L; Yan, Xiaofang; Guan, Wenchi; Li, Jing; Li, Xi; Spertus, John A; Masoudi, Frederick A; Krumholz, Harlan M; Jiang, Lixin

2017-12-21

Mobile health interventions have the potential to promote risk factor management and lifestyle modification, and are a particularly attractive approach for scaling across healthcare systems with limited resources. We are conducting two randomised trials to evaluate the efficacy of text message-based health messages in improving secondary coronary heart disease (CHD) prevention among patients with or without diabetes. The Cardiovascular Health And Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study are multicentre, single-blind, randomised controlled trials of text messaging versus standard treatment with 6 months of follow-up conducted in 37 hospitals throughout 17 provinces in China. The intervention group receives six text messages per week which target blood pressure control, medication adherence, physical activity, smoking cessation (when appropriate), glucose monitoring and lifestyle recommendations including diet (in CHAT-DM). The text messages were developed based on behavioural change techniques, using models such as the information-motivation-behavioural skills model, goal setting and provision of social support. A total sample size of 800 patients would be adequate for CHAT Study and sample size of 500 patients would be adequate for the CHAT-DM Study. In CHAT, the primary outcome is the change in systolic blood pressure (SBP) at 6 months. Secondary outcomes include a change in proportion of patients achieving a SBP <140 mm Hg, low-density lipoprotein cholesterol (LDL-C), physical activity, medication adherence, body mass index (BMI) and smoking cessation. In CHAT-DM, the primary outcome is the change in glycaemic haemoglobin (HbA 1C ) at 6 months. Secondary outcomes include a change in the proportion of patients achieving HbA 1C <7%, fasting blood glucose, SBP, LDL-C, BMI, physical activity and medication adherence. The central ethics committee at the China National Center for Cardiovascular Disease and the Yale University

Medical and biomedical research productivity from Palestine, 2002 - 2011.

PubMed

Sweileh, Waleed M; Zyoud, Sa'ed H; Sawalha, Ansam F; Abu-Taha, Adham; Hussein, Ayman; Al-Jabi, Samah W

2013-02-02

Medical research productivity reflects the level of medical education and practice in a particular country. The objective of this study was to examine the quantity and quality of medical and biomedical research published from Palestine. Comprehensive review of the literature indexed by Scopus was conducted. Data from Jan 01, 2002 till December 31, 2011 was searched for authors affiliated with Palestine or Palestinian authority. Results were refined to limit the search to medical and biomedical subjects. The quality of publication was assessed using Journal Citation Report. The total number of publications was 2207. A total of 770 publications were in the medical and biomedical subject areas. The annual rate of publication was 0.077 articles per gross domestic product/capita. The 770 publications have an h-index of 32. One hundred and thirty eight (18%) articles were published in 46 journals that were not indexed in the web of knowledge. Twenty two (22/770; 2.9%) articles were published in journals with an IF > 10. The quantity and quality of research originating from Palestinian institutions is promising given the scarce resources of Palestine. However, more effort is needed to bridge the gap in medical research productivity and to promote better health in Palestine.

A Mis-recognized Medical Vocabulary Correction System for Speech-based Electronic Medical Record

PubMed Central

Seo, Hwa Jeong; Kim, Ju Han; Sakabe, Nagamasa

2002-01-01

Speech recognition as an input tool for electronic medical record (EMR) enables efficient data entry at the point of care. However, the recognition accuracy for medical vocabulary is much poorer than that for doctor-patient dialogue. We developed a mis-recognized medical vocabulary correction system based on syllable-by-syllable comparison of speech text against medical vocabulary database. Using specialty medical vocabulary, the algorithm detects and corrects mis-recognized medical vocabularies in narrative text. Our preliminary evaluation showed 94% of accuracy in mis-recognized medical vocabulary correction.

Comparison of information content of structured and narrative text data sources on the example of medication intensification.

PubMed

Turchin, Alexander; Shubina, Maria; Breydo, Eugene; Pendergrass, Merri L; Einbinder, Jonathan S

2009-01-01

OBJECTIVE To compare information obtained from narrative and structured electronic sources using anti-hypertensive medication intensification as an example clinical issue of interest. DESIGN A retrospective cohort study of 5,634 hypertensive patients with diabetes from 2000 to 2005. MEASUREMENTS The authors determined the fraction of medication intensification events documented in both narrative and structured data in the electronic medical record. The authors analyzed the relationship between provider characteristics and concordance between intensifications in narrative and structured data. As there is no gold standard data source for medication information, the authors clinically validated medication intensification information by assessing the relationship between documented medication intensification and the patients' blood pressure in univariate and multivariate models. RESULTS Overall, 5,627 (30.9%) of 18,185 medication intensification events were documented in both sources. For a medication intensification event documented in narrative notes the probability of a concordant entry in structured records increased by 11% for each study year (p < 0.0001) and decreased by 19% for each decade of provider age (p = 0.035). In a multivariate model that adjusted for patient demographics and intraphysician correlations, an increase of one medication intensification per month documented in either narrative or structured data were associated with a 5-8 mm Hg monthly decrease in systolic and 1.5-4 mm Hg decrease in diastolic blood pressure (p < 0.0001 for all). CONCLUSION Narrative and structured electronic data sources provide complementary information on anti-hypertensive medication intensification. Clinical validity of information in both sources was demonstrated by correlation with changes in blood pressure.

CRIE: An automated analyzer for Chinese texts.

PubMed

Sung, Yao-Ting; Chang, Tao-Hsing; Lin, Wei-Chun; Hsieh, Kuan-Sheng; Chang, Kuo-En

2016-12-01

Textual analysis has been applied to various fields, such as discourse analysis, corpus studies, text leveling, and automated essay evaluation. Several tools have been developed for analyzing texts written in alphabetic languages such as English and Spanish. However, currently there is no tool available for analyzing Chinese-language texts. This article introduces a tool for the automated analysis of simplified and traditional Chinese texts, called the Chinese Readability Index Explorer (CRIE). Composed of four subsystems and incorporating 82 multilevel linguistic features, CRIE is able to conduct the major tasks of segmentation, syntactic parsing, and feature extraction. Furthermore, the integration of linguistic features with machine learning models enables CRIE to provide leveling and diagnostic information for texts in language arts, texts for learning Chinese as a foreign language, and texts with domain knowledge. The usage and validation of the functions provided by CRIE are also introduced.

Protocol to describe the analysis of text-based communication in medical records for patients discharged from intensive care to hospital ward.

PubMed

Parsons Leigh, Jeanna; Brown, Kyla; Buchner, Denise; Stelfox, Henry T

2016-07-08

Effective communication during hospital transitions of patient care is fundamental to ensuring patient safety and continuity of quality care. This study will describe text-based communication included in patient medical records before, during and after patient transfer from the intensive care unit (ICU) to a hospital ward (n=10 days) by documenting (1) the structure and focus of physician progress notes within and between medical specialties, (2) the organisation of subjective and objective information, including the location and accessibility of patient data and whether/how this changes during the hospital stay and (3) missing, illegible and erroneous information. This study is part of a larger mixed methods prospective observational study of ICU to hospital ward transfer practices in 10 ICUs across Canada. Medical records will be collected and photocopied for each consenting patient for a period of up to 10 consecutive days, including the final 2 days in the ICU, the day of transfer and the first 7 days on the ward (n=10 days). Textual analysis of medical record data will be completed by 2 independent reviewers to describe communication between stakeholders involved in ICU transfer. Research ethics board approval has been obtained at all study sites, including the coordinating study centre (which covers 4 Calgary-based sites; UofC REB 13-0021) and 6 additional study sites (UofA Pro00050646; UBC PHC Hi4-01667; Sunnybrook 336-2014; QCH 20140345-01H; Sherbrooke 14-172; Laval 2015-2171). Findings from this study will inform the development of an evidence-based tool that will be used to systematically analyse the series of notes in a patient's medical record. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

An index to characterize female career promotion in academic medicine.

PubMed

Brüggmann, Dörthe; Groneberg, David A

2017-01-01

Imbalances in female career promotion are a key factor of gender disparities at the workplace. They may lead to stress and stress-related diseases including burnout, depression or cardiovascular diseases. Since this problem cannot be generalized and varies between different fields, new approaches are needed to assess and describe the magnitude of the problem in single fields of work. To construct a new index, operating figures of female and male medical students were collected for Germany in a period over 15 years and their progression throughout their studies towards specialization and academic chair positions. By the use of different female to male ratios (f:m), we constructed an index that describes the extend by which women can ascent in their academic career by using the field of academic medicine as an example. A medical student f:m ratio of 1.54 (52,366 female vs. 34,010 male) was found for Germany in 2013. In 1998, this f:m ratio was 0.999. In the same year (2013), the OB/GYN hospital specialists' f:m ratio was 1.566 (3347 female vs. 2137 male physicians) and 0.577 (516 female vs 894 male physicians) for ENT hospital specialists, respectively. The f:m ratios concerning chairs of OB/GYN and ENT were 0.105 and 0.1, respectively. Then an index was generated that incorporated these operating figures with the student f:m ratio as denominator and the chair f:m ratio as numerator while the hospital specialist f:m ratio served as a corrector in the numerator in order to adjust to the attraction of a given field to female physicians. As a result, the index was 0.044 for OB/GYN and 0.113 for ENT instead of ideally ~1 in a completely gender harmonized situation. In summary, a new index to describe female career advancement was established for academic medicine. By the use of this index, different academic and medical fields can now be compared to each other and future benchmarks could be proposed. Also, country differences may be examined using the proposed index and

A comparison of two emergency medical dispatch protocols with respect to accuracy.

PubMed

Torlén, Klara; Kurland, Lisa; Castrén, Maaret; Olanders, Knut; Bohm, Katarina

2017-12-29

Emergency medical dispatching should be as accurate as possible in order to ensure patient safety and optimize the use of ambulance resources. This study aimed to compare the accuracy, measured as priority level, between two Swedish dispatch protocols - the three-graded priority protocol Medical Index and a newly developed prototype, the four-graded priority protocol, RETTS-A. A simulation study was carried out at the Emergency Medical Communication Centre (EMCC) in Stockholm, Sweden, between October and March 2016. Fifty-three voluntary telecommunicators working at SOS Alarm were recruited nationally. Each telecommunicator handled 26 emergency medical calls, simulated by experienced standard patients. Manuscripts for the scenarios were based on recorded real-life calls, representing the six most common complaints. A cross-over design with 13 + 13 calls was used. Priority level and medical condition for each scenario was set through expert consensus and used as gold standard in the study. A total of 1293 calls were included in the analysis. For priority level, n = 349 (54.0%) of the calls were assessed correctly with Medical Index and n = 309 (48.0%) with RETTS-A (p = 0.012). Sensitivity for the highest priority level was 82.6% (95% confidence interval: 76.6-87.3%) in the Medical Index and 54.0% (44.3-63.4%) in RETTS-A. Overtriage was 37.9% (34.2-41.7%) in the Medical Index and 28.6% (25.2-32.2%) in RETTS-A. The corresponding proportion of undertriage was 6.3% (4.7-8.5%) and 23.4% (20.3-26.9%) respectively. In this simulation study we demonstrate that Medical Index had a higher accuracy for priority level and less undertriage than the new prototype RETTS-A. The overall accuracy of both protocols is to be considered as low. Overtriage challenges resource utilization while undertriage threatens patient safety. The results suggest that in order to improve patient safety both protocols need revisions in order to guarantee safe emergency medical

Clinical Trial Research on Mongolian Medical Warm Acupuncture in Treating Insomnia.

PubMed

Bo, Agula; Si, Lengge; Wang, Yuehong; Xiu, Lan; Wu, Rihan; Li, Yutang; Mu, Rigenjiya; Ga, Latai; Miao, Mei; Shuang, Fu; Wu, Yunhua; Jin, Qiu; Tong, Suocai; Wuyun, Gerile; Guan, Wurihan; Mo, Rigen; Hu, Sileng; Zhang, Lixia; Peng, Rui; Bao, Lidao

2016-01-01

Objective. Insomnia is one of the most common sleep disorders. Hypnotics have poor long-term efficacy. Mongolian medical warm acupuncture has significant efficacy in treating insomnia. The paper evaluates the role of Mongolian medical warm acupuncture in treating insomnia by investigating the Mongolian medicine syndromes and conditions, Pittsburgh sleep quality index, and polysomnography indexes. Method. The patients were diagnosed in accordance with International Classification of Sleep Disorders (ICSD-2). The insomnia patients were divided into the acupuncture group (40 cases) and the estazolam group (40 cases). The patients underwent intervention of Mongolian medical warm acupuncture and estazolam. The indicators of the Mongolian medicine syndromes and conditions, Pittsburgh sleep quality index (PSQI), and polysomnography indexes (PSG) have been detected. Result. Based on the comparison of the Mongolian medicine syndrome scores between the warm acupuncture group and the drug treatment group, the result indicated P < 0.01. The clinical efficacy result showed that the effective rate (85%) in the warm acupuncture group was higher than that (70%) in the drug group. The total scores of PSQI of both groups were approximated. The sleep quality indexes of both groups decreased significantly ( P < 0.05). The sleep quality index in the Mongolian medical warm acupuncture group decreased significantly ( P < 0.01) and was better than that in the estazolam group. The sleep efficiency and daytime functions of the patients in the Mongolian medical warm acupuncture group improved significantly ( P < 0.01). The sleep time was significantly extended ( P < 0.01) in the Mongolian medical warm acupuncture group following PSG intervention. The sleep time during NREM in the Mongolian warm acupuncture group increased significantly ( P < 0.01). The sleep time exhibited a decreasing trend during REM and it decreased significantly in the Mongolian warm acupuncture group ( P < 0.01). The

Seventy Years of the Journal “Medical Archives”

PubMed Central

Masic, Izet

2016-01-01

This year journal “Medical Archives” celebrates 70th anniversary of its continuing publication. Medical Archives is oldest biomedical journal in Bosnia and Herzegovina and one of the oldest medical journals in Europe, established in the year 1947, as official scientific and professional journal of Association of Physicians of Bosnia and Herzegovina. Until present Medical Archives has published over 5000 articles. Today Medical Archives is internationally recognized medical peer-reviewed indexed journal, visible in more than 30 international on-line databases. PMID:26980925

Work Ability Index predicts application for disability pension after work-related medical rehabilitation for chronic back pain.

PubMed

Bethge, Matthias; Gutenbrunner, Christoph; Neuderth, Silke

2013-11-01

To determine whether the Work Ability Index (WAI), a short 7-item self-report questionnaire addressing issues of perceived disability, impairment, and expectations for resuming work, predicts application for disability pension, recommendations for further treatment, and other adverse work-related criteria in patients with chronic back pain after rehabilitation. Cohort study with 3-month follow-up. Seven inpatient rehabilitation centers. Patients (N=294; 168 women; mean age, 49.9y) with chronic back pain. The WAI was completed at the beginning of rehabilitation. All patients were treated according to the German rehabilitation guidelines for chronic back pain and work-related medical rehabilitation. Application for disability pension, as assessed by a postal questionnaire 3 months after discharge. Receiver operating characteristic curve analysis of the association between the WAI at baseline and subsequent application for disability pension revealed an area under the curve of .80 (95% confidence interval [CI], .62-.97). Youden index was highest when the WAI cutoff value was ≤20 points (sensitivity, 72.7%; specificity, 82.2%; total correct classification, 81.7%). After adjusting for age and sex, persons with a baseline WAI score of ≤20 points had 15.6 times (95% CI, 3.6-68.2) higher odds of subsequent application for disability pension, 4.9 times (95% CI, 1.5-16.8) higher odds of unemployment, and 6 times (95% CI, 2.4-15.2) higher odds of long-term sick leave at follow-up. The WAI could help rehabilitation professionals identify patients with back pain with a high risk of a subsequent application for disability pension. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

PubMed

Lin, Frank Po-Yen; Pokorny, Adrian; Teng, Christina; Epstein, Richard J

2017-07-31

Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical narratives, we have built a novel computational pipeline termed Text-based Exploratory Pattern Analyser for Prognosticator and Associator discovery (TEPAPA). This pipeline combines semantic-free natural language processing (NLP), regular expression induction, and statistical association testing to identify conserved text patterns associated with outcome variables of clinical interest. When we applied TEPAPA to a cohort of head and neck squamous cell carcinoma patients, plausible concepts known to be correlated with human papilloma virus (HPV) status were identified from the EMR text, including site of primary disease, tumour stage, pathologic characteristics, and treatment modalities. Similarly, correlates of other variables (including gender, nodal status, recurrent disease, smoking and alcohol status) were also reliably recovered. Using highly-associated patterns as covariates, a patient's HPV status was classifiable using a bootstrap analysis with a mean area under the ROC curve of 0.861, suggesting its predictive utility in supporting EMR-based phenotyping tasks. These data support using this integrative approach to efficiently identify disease-associated factors from unstructured EMR narratives, and thus to efficiently generate testable hypotheses.

Costs of venous thromboembolism associated with hospitalization for medical illness.

PubMed

Cohoon, Kevin P; Leibson, Cynthia L; Ransom, Jeanine E; Ashrani, Aneel A; Petterson, Tanya M; Long, Kirsten Hall; Bailey, Kent R; Heit, Johm A

2015-04-01

To determine population-based estimates of medical costs attributable to venous thromboembolism (VTE) among patients currently or recently hospitalized for acute medical illness. Population-based cohort study conducted in Olmsted County, Minnesota. Using Rochester Epidemiology Project (REP) resources, we identified all Olmsted County residents with objectively diagnosed incident VTE during or within 92 days of hospitalization for acute medical illness over the 18-year period of 1988 to 2005 (n=286). One Olmsted County resident hospitalized for medical illness without VTE was matched to each case for event date (±1 year), duration of prior medical history, and active cancer status. Subjects were followed forward in REP provider-linked billing data for standardized, inflation-adjusted direct medical costs (excluding outpatient pharmaceutical costs) from 1 year before their respective event or index date to the earliest of death, emigration from Olmsted County, or December 31, 2011 (study end date). We censored follow-up such that each case and matched control had similar periods of observation. We used generalized linear modeling (controlling for age, sex, preexisting conditions, and costs 1 year before index) to predict costs for cases and controls. Adjusted mean predicted costs were 2.5-fold higher for cases ($62,838) than for controls ($24,464) (P<.001) from index to up to 5 years post index. Cost differences between cases and controls were greatest within the first 3 months after the event date (mean difference=$16,897) but costs remained significantly higher for cases compared with controls for up to 3 years. VTE during or after recent hospitalization for medical illness contributes a substantial economic burden.

[Criteria of estimation of state forensic-medical expert activity administration].

PubMed

Klevno, V A; Loban, I E

2008-01-01

Criteria of estimation of state forensic medical activity administration were systematized and their content was considered. New integral index of administration efficiency - index of technological efficiency - was developed and proved.

Design and rationale of the Cardiovascular Health and Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study: two randomised controlled trials of text messaging to improve secondary prevention for coronary heart disease and diabetes

PubMed Central

Huo, Xiqian; Spatz, Erica S; Ding, Qinglan; Horak, Paul; Zheng, Xin; Masters, Claire; Zhang, Haibo; Irwin, Melinda L; Yan, Xiaofang; Guan, Wenchi; Li, Jing; Li, Xi; Spertus, John A; Masoudi, Frederick A; Krumholz, Harlan M; Jiang, Lixin

2017-01-01

Introduction Mobile health interventions have the potential to promote risk factor management and lifestyle modification, and are a particularly attractive approach for scaling across healthcare systems with limited resources. We are conducting two randomised trials to evaluate the efficacy of text message-based health messages in improving secondary coronary heart disease (CHD) prevention among patients with or without diabetes. Methods and analysis The Cardiovascular Health And Text Messaging (CHAT) Study and the CHAT-Diabetes Mellitus (CHAT-DM) Study are multicentre, single-blind, randomised controlled trials of text messaging versus standard treatment with 6 months of follow-up conducted in 37 hospitals throughout 17 provinces in China. The intervention group receives six text messages per week which target blood pressure control, medication adherence, physical activity, smoking cessation (when appropriate), glucose monitoring and lifestyle recommendations including diet (in CHAT-DM). The text messages were developed based on behavioural change techniques, using models such as the information-motivation-behavioural skills model, goal setting and provision of social support. A total sample size of 800 patients would be adequate for CHAT Study and sample size of 500 patients would be adequate for the CHAT-DM Study. In CHAT, the primary outcome is the change in systolic blood pressure (SBP) at 6 months. Secondary outcomes include a change in proportion of patients achieving a SBP <140 mm Hg, low-density lipoprotein cholesterol (LDL-C), physical activity, medication adherence, body mass index (BMI) and smoking cessation. In CHAT-DM, the primary outcome is the change in glycaemic haemoglobin (HbA1C) at 6 months. Secondary outcomes include a change in the proportion of patients achieving HbA1C<7%, fasting blood glucose, SBP, LDL-C, BMI, physical activity and medication adherence. Ethics and dissemination The central ethics committee at the China National Center for

Influence of national culture on the adoption of integrated medical curricula.

PubMed

Jippes, Mariëlle; Majoor, Gerard D

2011-03-01

Integrated curricula have been implemented in medical schools all over the world. However, among countries different relative numbers of schools with integrated curricula are found. This study aims to explore the possible correlation between the percentage of medical schools with integrated curricula in a country and that country's cultural characteristics. Curricula were defined as not integrated if in the first 2 years of the program at least two out of the three monodisciplinary courses Anatomy, Physiology and Biochemistry were identified. Culture was defined using Hofstede's dimensions Power distance, Uncertainty avoidance, Masculinity/Femininity, and Individualism/Collectivism. Consequently, this study had to be restricted to the 63 countries included in Hofstede's studies which harbored 1,195 medical schools. From each country we randomly sampled a maximum of 15 schools yielding 484 schools to be investigated. In total 91% (446) of the curricula were found. Correlation of percent integrated curricula and each dimension of culture was determined by calculating Spearman's Rho. A high score on the Power distance index and a high score on the Uncertainty avoidance index correlated with a low percent integrated curricula; a high score on the Individualism index correlated with a high percent integrated curricula. The percentage integrated curricula in a country did not correlate with its score on the Masculinity index. National culture is associated with the propensity of medical schools to adopt integrated medical curricula. Consequently, medical schools considering introduction of integrated and problem-based medical curricula should take into account dimensions of national culture which may hinder the innovation process.

Medical and biomedical research productivity from Palestine, 2002 – 2011

PubMed Central

2013-01-01

Background Medical research productivity reflects the level of medical education and practice in a particular country. The objective of this study was to examine the quantity and quality of medical and biomedical research published from Palestine. Findings Comprehensive review of the literature indexed by Scopus was conducted. Data from Jan 01, 2002 till December 31, 2011 was searched for authors affiliated with Palestine or Palestinian authority. Results were refined to limit the search to medical and biomedical subjects. The quality of publication was assessed using Journal Citation Report. The total number of publications was 2207. A total of 770 publications were in the medical and biomedical subject areas. The annual rate of publication was 0.077 articles per gross domestic product/capita. The 770 publications have an h-index of 32. One hundred and thirty eight (18%) articles were published in 46 journals that were not indexed in the web of knowledge. Twenty two (22/770; 2.9%) articles were published in journals with an IF > 10. Conclusions The quantity and quality of research originating from Palestinian institutions is promising given the scarce resources of Palestine. However, more effort is needed to bridge the gap in medical research productivity and to promote better health in Palestine. PMID:23375070

Awareness of academic use of smartphones and medical apps among medical students in a private medical college?

PubMed

Shah, Jehanzaib; Haq, Usman; Bashir, Ali; Shah, Syed Aslam

2016-02-01

To assess the awareness of medical apps and academic use of smartphones among medical students. The questionnaire-based descriptive cross-sectional study was conducted in January 2015 and comprised medical students of the Rawal Institute of Health Sciences, Islamabad, Pakistan. The self-designed questionnaire was reviewed by a panel of expert for content reliability and validity. Questionnaires were distributed in the classrooms and were filled by the students anonymously. SPSS 16 was used for statistical analysis. Among the 569 medical students in the study, 545 (95.8%) had smartphones and 24(4.2%) were using simple cell phones. Overall, 226(41.46%) of the smart phone users were using some medical apps. Besides, 137(24.08%) were aware of the medical apps but were not using them. Also, 391(71.7%) students were not using any type of medical text eBooks through their phone, and only 154(28.3%) had relevant text eBooks in their phones. Medical college students were using smartphones mostly as a means of telecommunication rather than a gadget for improving medical knowledge.

NASA's online machine aided indexing system

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1993-01-01

This report describes the NASA Lexical Dictionary, a machine aided indexing system used online at the National Aeronautics and Space Administration's Center for Aerospace Information (CASI). This system is comprised of a text processor that is based on the computational, non-syntactic analysis of input text, and an extensive 'knowledge base' that serves to recognize and translate text-extracted concepts. The structure and function of the various NLD system components are described in detail. Methods used for the development of the knowledge base are discussed. Particular attention is given to a statistically-based text analysis program that provides the knowledge base developer with a list of concept-specific phrases extracted from large textual corpora. Production and quality benefits resulting from the integration of machine aided indexing at CASI are discussed along with a number of secondary applications of NLD-derived systems including on-line spell checking and machine aided lexicography.

Association Between Study Quality and Publication Rates of Medical Education Abstracts Presented at the Society of General Internal Medicine Annual Meeting.

PubMed

Sawatsky, Adam P; Beckman, Thomas J; Edakkanambeth Varayil, Jithinraj; Mandrekar, Jayawant N; Reed, Darcy A; Wang, Amy T

2015-08-01

Studies reveal that 44.5% of abstracts presented at national meetings are subsequently published in indexed journals, with lower rates for abstracts of medical education scholarship. We sought to determine whether the quality of medical education abstracts is associated with subsequent publication in indexed journals, and to compare the quality of medical education abstracts presented as scientific abstracts versus innovations in medical education (IME). Retrospective cohort study. Medical education abstracts presented at the Society of General Internal Medicine (SGIM) 2009 annual meeting. Publication rates were measured using database searches for full-text publications through December 2013. Quality was assessed using the validated Medical Education Research Study Quality Instrument (MERSQI). Overall, 64 (44%) medical education abstracts presented at the 2009 SGIM annual meeting were subsequently published in indexed medical journals. The MERSQI demonstrated good inter-rater reliability (intraclass correlation range, 0.77-1.00) for grading the quality of medical education abstracts. MERSQI scores were higher for published versus unpublished abstracts (9.59 vs. 8.81, p = 0.03). Abstracts with a MERSQI score of 10 or greater were more likely to be published (OR 3.18, 95% CI 1.47-6.89, p = 0.003). ). MERSQI scores were higher for scientific versus IME abstracts (9.88 vs. 8.31, p < 0.001). Publication rates were higher for scientific abstracts (42 [66%] vs. 37 [46%], p = 0.02) and oral presentations (15 [23%] vs. 6 [8%], p = 0.01). The publication rate of medical education abstracts presented at the 2009 SGIM annual meeting was similar to reported publication rates for biomedical research abstracts, but higher than publication rates reported for medical education abstracts. MERSQI scores were associated with higher abstract publication rates, suggesting that attention to measures of quality--such as sampling, instrument validity, and data analysis

Intelligent medical information filtering.

PubMed

Quintana, Y

1998-01-01

This paper describes an intelligent information filtering system to assist users to be notified of updates to new and relevant medical information. Among the major problems users face is the large volume of medical information that is generated each day, and the need to filter and retrieve relevant information. The Internet has dramatically increased the amount of electronically accessible medical information and reduced the cost and time needed to publish. The opportunity of the Internet for the medical profession and consumers is to have more information to make decisions and this could potentially lead to better medical decisions and outcomes. However, without the assistance from professional medical librarians, retrieving new and relevant information from databases and the Internet remains a challenge. Many physicians do not have access to the services of a medical librarian. Most physicians indicate on surveys that they do not prefer to retrieve the literature themselves, or visit libraries because of the lack of recent materials, poor organisation and indexing of materials, lack of appropriate and available material, and lack of time. The information filtering system described in this paper records the online web browsing behaviour of each user and creates a user profile of the index terms found on the web pages visited by the user. A relevance-ranking algorithm then matches the user profiles to the index terms of new health care web pages that are added each day. The system creates customised summaries of new information for each user. A user can then connect to the web site to read the new information. Relevance feedback buttons on each page ask the user to rate the usefulness of the page to their immediate information needs. Errors in relevance ranking are reduced in this system by having both the user profile and medical information represented in the same representation language using a controlled vocabulary. This system also updates the user profiles

Short Text Messages (SMS) as an Additional Tool for Notifying Medical Staff in Case of a Hospital Mass Casualty Incident.

PubMed

Timler, Dariusz; Bogusiak, Katarzyna; Kasielska-Trojan, Anna; Neskoromna-Jędrzejczak, Aneta; Gałązkowski, Robert; Szarpak, Łukasz

2016-02-01

The aim of the study was to verify the effectiveness of short text messages (short message service, or SMS) as an additional notification tool in case of fire or a mass casualty incident in a hospital. A total of 2242 SMS text messages were sent to 59 hospital workers divided into 3 groups (n=21, n=19, n=19). Messages were sent from a Samsung GT-S8500 Wave cell phone and Orange Poland was chosen as the telecommunication provider. During a 3-month trial period, messages were sent between 3:35 PM and midnight with no regular pattern. Employees were asked to respond by telling how much time it would take them to reach the hospital in case of a mass casualty incident. The mean reaction time (SMS reply) was 36.41 minutes. The mean declared time of arrival to the hospital was 100.5 minutes. After excluding 10% of extreme values for declared arrival time, the mean arrival time was estimated as 38.35 minutes. Short text messages (SMS) can be considered an additional tool for notifying medical staff in case of a mass casualty incident.

Validation of an Improved Computer-Assisted Technique for Mining Free-Text Electronic Medical Records.

PubMed

Duz, Marco; Marshall, John F; Parkin, Tim

2017-06-29

The use of electronic medical records (EMRs) offers opportunity for clinical epidemiological research. With large EMR databases, automated analysis processes are necessary but require thorough validation before they can be routinely used. The aim of this study was to validate a computer-assisted technique using commercially available content analysis software (SimStat-WordStat v.6 (SS/WS), Provalis Research) for mining free-text EMRs. The dataset used for the validation process included life-long EMRs from 335 patients (17,563 rows of data), selected at random from a larger dataset (141,543 patients, ~2.6 million rows of data) and obtained from 10 equine veterinary practices in the United Kingdom. The ability of the computer-assisted technique to detect rows of data (cases) of colic, renal failure, right dorsal colitis, and non-steroidal anti-inflammatory drug (NSAID) use in the population was compared with manual classification. The first step of the computer-assisted analysis process was the definition of inclusion dictionaries to identify cases, including terms identifying a condition of interest. Words in inclusion dictionaries were selected from the list of all words in the dataset obtained in SS/WS. The second step consisted of defining an exclusion dictionary, including combinations of words to remove cases erroneously classified by the inclusion dictionary alone. The third step was the definition of a reinclusion dictionary to reinclude cases that had been erroneously classified by the exclusion dictionary. Finally, cases obtained by the exclusion dictionary were removed from cases obtained by the inclusion dictionary, and cases from the reinclusion dictionary were subsequently reincluded using Rv3.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Manual analysis was performed as a separate process by a single experienced clinician reading through the dataset once and classifying each row of data based on the interpretation of the free-text

The Index Medicus: Why It Works and When It Doesn't *

PubMed Central

Jackson, Mary F.

1966-01-01

A user study of the Index Medicus done at the Walter Reed Army Medical Center included responses from a group of sixty researchers, clinicians, residents, and interns. An analysis of the questionnaire shows that, while all respondents use the Index Medicus, most use it to search for a specific subject or a specific author reference. Comments received were critical of the delay from the time of journal publication until the appearance of its citation in Index Medicus. Suggestions were offered concerning the type of publication most of the respondents would prefer. PMID:5921472

Francisco Vallés and the Renaissance reinterpretation of Aristotle's Meteorologica IV as a medical text.

PubMed

Martin, Craig

2002-01-01

In this paper I describe the context and goals of Francisco Vallés In IV librum Meteorologicorum commentaria (1558). Vallés' work stands as a landmark because it interprets a work of Aristotle's natural philosophy specifically for medical doctors and medical theory. Vallés' commentary is representative of new understandings of Galenic-Hippocratic medicine that emerged as a result of expanding textual knowledge. These approaches are evident in a number of sixteenth-century commentaries on Meteorologica IV; in particular the works of Pietro Pomponazzi, Lodovico Boccadiferro, Jacob Schegk, and Francesco Vimercati. Vallés' conviction that Meteorologica IV is relevant to medical knowledge depends on his understanding of Aristotle's theory of homeomerous substances and their relation to composite substances. The application of Meteorologica IV to medical topics became commonplace in the following years, and this Aristotelian book became widely known as a bridge between natural philosophy and medicine.

Representing the Other in Sociology of the Family Texts

ERIC Educational Resources Information Center

Dunham, Charlotte Chorn; Cannon, Julie Harms; Dietz, Bernadette

2004-01-01

The purpose of this paper is to explore the concept of otherness as it applies to the content of sociology of the family texts. We conducted a study of the content of the indexes and the body of texts on sociology of the family, examining the way in which the experiences of whites were addressed relative to families of color. We found that whites…

Changes in medication use after dementia diagnosis in an observational cohort of diabetes patients

PubMed Central

Sarkar, Urmimala; Lyles, Courtney; Steinman, Michael; Huang, Elbert S.; Moffet, Howard H.; Whitmer, Rachel A.; Warton, E. Margaret; Karter, Andrew J.

2017-01-01

Background/objective Clinical guidelines recommend avoidance of polypharmacy in patients with dementia. We assessed changes in medication use following a diagnosis of dementia among patients with type 2 diabetes. Design Difference-in-differences analysis of pre-post changes in the number of dispensed chronic medications, comparing patients with and without newly diagnosed dementia. Setting Integrated health care delivery system, Kaiser Permanente Northern California (KPNC). Participants Patients with type 2 diabetes, enrolled in a baseline survey, ≥50 years of age without prevalent dementia. During 5 years of follow-up, we identified 193 patients with a new diagnosis of dementia and used risk-set sampling to randomly select 5 reference subjects per case, matched on 5-year age categories and sex (965 matched patients). This resulted in an analytic sample of 1,158. Measurements The exposure was new diagnosis of dementia. Our primary outcome was the change in the number (count) of current chronic medications (total, cardiovascular (blood pressure and lipid control), and diabetes) at three time points: (a) pre-index date (one year prior to the index date); (b) index date (date of diagnosis of dementia or matched reference date); and (c) post-index date (up to one year subsequent to the index date). Results After adjustment, the overall number of chronic medications and the subset of cardiovascular medications declined following a dementia diagnosis and among age, sex, and time-matched reference individuals, but the decline was significantly greater among the dementia group (−0.71 medications compared to reference, p<0.05). The number of diabetes medications declined in both groups, but the declines were not statistically different (−0.18 medications compared to reference, p<0.05). Conclusions Patients and their providers reduced use of cardio-metabolic medications subsequent to a diagnosis of dementia as recommended in national guidelines. PMID:27642180

Longitudinal Analysis of Gender Differences in Academic Productivity among Medical Faculty across 24 Medical Schools in the United States

PubMed Central

Raj, Anita; Carr, Phyllis L.; Kaplan, Samantha E.; Terrin, Norma; Breeze, Janis L.; Freund, Karen M.

2017-01-01

Purpose This study examines gender differences in academic productivity, as indicated by publications and federal grant funding acquisition, among a longitudinal cohort of medical faculty from 24 medical schools across the United States, 1995 to 2012. Method Data for this research was taken from the National Faculty Study involving a survey with medical faculty recruited from medical schools in 1995, and followed up in 2012. Data included surveys and publication and grant funding databases. Outcomes were number of publications, h-index and principal investigator on a federal grant in the prior two years. Gender differences were assessed using negative binomial regression models for publication and h-index outcomes, and logistic regression for the grant funding outcome; analyses adjusted for race/ethnicity, rank, specialty area and years since first academic appointment. Results Data were available for 1,244 of the 1,275 (98%) subjects eligible for the follow up study. Men were significantly more likely than women to be married/partnered, have children, and hold the rank of professor (P < .0001). Adjusted regression models document that women have a lower rate of publication (relative number = .71; 95% CI = .63, .81; P < .0001) and h-index (relative number = .81; 95% CI = .73, .90; P < .0001) relative to men, though there was no gender difference in grant funding. Conclusions Women faculty acquire federal funding at similar rates as male faculty, yet lag behind in terms of publications and their impact. Medical academia must consider how to help address ongoing gender disparities in publication records. PMID:27276002

Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

PubMed

Dziadek, Juliusz; Henriksson, Aron; Duneld, Martin

2017-01-01

The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary.

BROWSER: An Automatic Indexing On-Line Text Retrieval System. Annual Progress Report.

ERIC Educational Resources Information Center

Williams, J. H., Jr.

The development and testing of the Browsing On-line With Selective Retrieval (BROWSER) text retrieval system allowing a natural language query statement and providing on-line browsing capabilities through an IBM 2260 display terminal is described. The prototype system contains data bases of 25,000 German language patent abstracts, 9,000 English…

Performance of Malaysian Medical Journals

PubMed Central

Abrizah, Abdullah

2016-01-01

Indexation status matters for scholarly journal prestige and trust. The performance of Malaysian medical journals at the international level is gauged through the global citation databases, and at the national level through MyCite, a national citation indexing system. The performance indicators include journals publication productivity, the citations they garner, and their scores on other bibliometric indices such as journal impact factor (IF), and h-index. There is a growing consciousness amongst journal editorials to improve quality and increase chances of getting indexed in MyCite. Although it is now possible to gauge journal performance within Malaysia, through MyCite, the government and public are concerned about journal performance in international databases. Knowing the performance of journals in MyCite will help the editors and publishers to improve the quality and visibility of Malaysian journals and strategise to bring their journal to the international level of indexation. PMID:27547108

Towards computational improvement of DNA database indexing and short DNA query searching.

PubMed

Stojanov, Done; Koceski, Sašo; Mileva, Aleksandra; Koceska, Nataša; Bande, Cveta Martinovska

2014-09-03

In order to facilitate and speed up the search of massive DNA databases, the database is indexed at the beginning, employing a mapping function. By searching through the indexed data structure, exact query hits can be identified. If the database is searched against an annotated DNA query, such as a known promoter consensus sequence, then the starting locations and the number of potential genes can be determined. This is particularly relevant if unannotated DNA sequences have to be functionally annotated. However, indexing a massive DNA database and searching an indexed data structure with millions of entries is a time-demanding process. In this paper, we propose a fast DNA database indexing and searching approach, identifying all query hits in the database, without having to examine all entries in the indexed data structure, limiting the maximum length of a query that can be searched against the database. By applying the proposed indexing equation, the whole human genome could be indexed in 10 hours on a personal computer, under the assumption that there is enough RAM to store the indexed data structure. Analysing the methodology proposed by Reneker, we observed that hits at starting positions [Formula: see text] are not reported, if the database is searched against a query shorter than [Formula: see text] nucleotides, such that [Formula: see text] is the length of the DNA database words being mapped and [Formula: see text] is the length of the query. A solution of this drawback is also presented.

How Twitter Is Studied in the Medical Professions: A Classification of Twitter Papers Indexed in PubMed

PubMed Central

2013-01-01

Background Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. Objective This paper aims to identify published work relating to Twitter within the fields indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Methods Papers on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain, and aspect. Results As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focused on Twitter (the others referring to it tangentially). The early Twitter focused papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that

How Twitter Is Studied in the Medical Professions: A Classification of Twitter Papers Indexed in PubMed.

PubMed

Williams, Shirley Ann; Terras, Melissa; Warwick, Claire

2013-01-01

Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. This paper aims to identify published work relating to Twitter within the fields indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Papers on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper's title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain, and aspect. As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focused on Twitter (the others referring to it tangentially). The early Twitter focused papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge

A Survey in Indexing and Searching XML Documents.

ERIC Educational Resources Information Center

Luk, Robert W. P.; Leong, H. V.; Dillon, Tharam S.; Chan, Alvin T. S.; Croft, W. Bruce; Allan, James

2002-01-01

Discussion of XML focuses on indexing techniques for XML documents, grouping them into flat-file, semistructured, and structured indexing paradigms. Highlights include searching techniques, including full text search and multistage search; search result presentations; database and information retrieval system integration; XML query languages; and…

Reorganized text.

PubMed

2015-05-01

Reorganized Text: In the Original Investigation titled “Patterns of Hospital Utilization for Head and Neck Cancer Care: Changing Demographics” posted online in the January 29, 2015, issue of JAMA Otolaryngology–Head & Neck Surgery (doi:10.1001 /jamaoto.2014.3603), information was copied within sections and text rearranged to accommodate Continuing Medical Education quiz formatting. The information from the topic statements of each paragraph in the Hypothesis Testing subsection of the Methods section was collected in a new first paragraph for that subsection, which reads as follows: “Several hypotheses regarding the causes of regionalization of HNCA care were tested using the NIS data: (1) increasing patient comorbidities over time, causing a shift in care to teaching institutions that would theoretically be better equipped to handle such increased comorbidities; (2) shifting of payer status; (3) increased proportion of prior radiation therapy; and (4) a higher fraction of more complex procedures being referred and performed at teaching institutions.” In addition, the phrase "As summarized in Table3," was added to the beginning of paragraph 6 of the Discussion section, and the call-out to Table 3 in the middle of that paragraph was deleted. Finally, paragraphs 6 and 7 of the Discussion section were combined.

[Unravelling medical leadership].

PubMed

Voogt, Judith J; van Rensen, Elizabeth L J; Noordegraaf, Mirko; Schneider, Margriet M E

2015-01-01

Medical leadership is a popular topic in the Netherlands, and several interest groups now incorporate medical leadership into postgraduate medical education. However, there is no consensus on what this concept entails. By conducting a discourse analysis, a qualitative method which uses language and text to reveal existing viewpoints, this article reveals three perspectives on medical leadership: administrative leadership, leadership within organisations and leadership within each doctor's daily practice. Text analysis shows that the first two perspectives refer to medical leadership mainly in a defensive manner: by demonstrating medical leadership doctors could 'take the lead' once again; patient care only seems to play a small part in the process. These perspectives are not free of consequences, they will determine how the medical profession is constructed. For this reason, it is argued that there should be more emphasis on the third perspective, in which the quality of care for patients is of primary importance.

LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data

PubMed Central

van Walraven, Carl; Wong, Jenna; Forster, Alan J

2012-01-01

Background Death or urgent readmission after hospital discharge is a common adverse event that can be used to compare outcomes of care between institutions. To accurately adjust for risk and to allow for interhospital comparisons of readmission rates, we used administrative data to derive and internally validate an extension of the LACE index, a previously validated index for 30-day death or urgent readmission. Methods We randomly selected 500 000 medical and surgical patients discharged to the community from any Ontario hospital between 1 April 2003 and 31 March 2009. We derived a logistic regression model on 250 000 randomly selected patients from this group and modified the final model into an index scoring system, the LACE+ index. We internally validated the LACE+ index using data from the remaining 250 000 patients and compared its performance with that of the original LACE index. Results Within 30 days of discharge to the community, 33 825 (6.8%) of the patients had died or had been urgently readmitted. In addition to the variables included in the LACE index (length of stay in hospital [L], acuity of admission [A], comorbidity [C] and emergency department utilization in the 6 months before admission [E]), the LACE+ index incorporated patient age and sex, teaching status of the discharge hospital, acute diagnoses and procedures performed during the index admission, number of days on alternative level of care during the index admission, and number of elective and urgent admissions to hospital in the year before the index admission. The LACE+ index was highly discriminative (C statistic 0.771, 95% confidence interval 0.767–0.775), was well calibrated across most of its range of scores and had a model performance that exceeded that of the LACE index. Interpretation The LACE+ index can be used to predict the risk of postdischarge death or urgent readmission on the basis of administrative data for the Ontario population. Its performance exceeds that of the LACE

Text mining for neuroanatomy using WhiteText with an updated corpus and a new web application

PubMed Central

French, Leon; Liu, Po; Marais, Olivia; Koreman, Tianna; Tseng, Lucia; Lai, Artemis; Pavlidis, Paul

2015-01-01

We describe the WhiteText project, and its progress towards automatically extracting statements of neuroanatomical connectivity from text. We review progress to date on the three main steps of the project: recognition of brain region mentions, standardization of brain region mentions to neuroanatomical nomenclature, and connectivity statement extraction. We further describe a new version of our manually curated corpus that adds 2,111 connectivity statements from 1,828 additional abstracts. Cross-validation classification within the new corpus replicates results on our original corpus, recalling 67% of connectivity statements at 51% precision. The resulting merged corpus provides 5,208 connectivity statements that can be used to seed species-specific connectivity matrices and to better train automated techniques. Finally, we present a new web application that allows fast interactive browsing of the over 70,000 sentences indexed by the system, as a tool for accessing the data and assisting in further curation. Software and data are freely available at http://www.chibi.ubc.ca/WhiteText/. PMID:26052282

Two thousand years of medical advice on breastfeeding: comparison of Chinese and western texts.

PubMed

Gartner, L M; Stone, C

1994-12-01

This discussion introduces only a few aspects of the historical writings on breastfeeding in the two cultures. Chinese writings seem to be closer in orientation to modern worldwide medical advice, approaching breastfeeding from a more natural and supportive perspective. Ancient and not-so-ancient western medical advice on breastfeeding often implies the inadequacy of the mother to breastfeed her own infant, especially in the early weeks of life. One can only speculate as to what the historical basis for this may be. European medicine emphasizes the testing of milk for its adequacy. Again, the scientific basis for this is not evident. Modern clinical science finds that the milk of virtually all mothers, even those suffering from significant malnutrition, is adequate for the growth and development of the infant. This focus on the "testing" of milk may represent an early example of the reliance on laboratory diagnosis that has so heavily dominated western medicine in recent years. Finally, western medicine seems more managerial with regard to breastfeeding than Chinese medicine, and has perhaps "medicalized" breastfeeding, a compliant often voiced even now in late 20th century America. Nonetheless, both literatures demonstrate that throughout the history of recorded medicine, physicians have been concerned with promoting optimal breastfeeding and have understood the importance of human milk for the survival, growth, and development of the infant.

Prognostic validation of the body mass index, airflow obstruction, dyspnea, and exercise capacity (BODE) index in inoperable non-small-cell lung cancer.

PubMed

Denehy, Linda; Hornsby, Whitney E; Herndon, James E; Thomas, Samantha; Ready, Neal E; Granger, Catherine L; Valera, Lauren; Kenjale, Aarti A; Eves, Neil D; Jones, Lee W

2013-12-01

To investigate the prognostic utility of the body mass index, severity of airflow obstruction, measures of exertional dyspnea, and exercise capacity (BODE) index in patients with inoperable non-small-cell lung cancer (NSCLC). One hundred consecutive patients with inoperable NSCLC and performance status 0 to 3 completed pulmonary function testing, the modified Medical Research Council dyspnea scale, a 6-minute walk test, and body mass index-the multidimensional 10-point BODE index. Cox proportional models were used to estimate the risk of all-cause mortality according to the BODE index with or without adjustment for traditional prognostic factors. Median follow-up was 31.5 months; 61 deaths (61%) were reported during this period. There was a significant univariate association between the BODE index score and mortality (adjusted p(trend) = 0.027). Compared with patients with a BODE index of 0, the adjusted hazard ratio for risk of death was 1.37 (95% confidence interval [CI], 0.74-2.55) for a BODE index of 1, 1.22 (95% CI, 0.45-3.25) for a BODE index of 2, and 2.44 (95% CI, 1.19-4.99) for a BODE index more than 2. The BODE index provided incremental prognostic information beyond that provided traditional markers of prognosis (adjusted p(trend) = 0.051). Every one-point increase in the BODE index, the risk of death increased by 25% (hazard ratio = 1.25; 95% CI, 1.27-4.64). The BODE index is a strong independent predictor of survival in inoperable NSCLC beyond traditional risk factors. Use of this multidimensional tool may improve risk stratification and prognostication in NSCLC.

CUQI: cardiac ultrasound video quality index

PubMed Central

Razaak, Manzoor; Martini, Maria G.

2016-01-01

Abstract. Medical images and videos are now increasingly part of modern telecommunication applications, including telemedicinal applications, favored by advancements in video compression and communication technologies. Medical video quality evaluation is essential for modern applications since compression and transmission processes often compromise the video quality. Several state-of-the-art video quality metrics used for quality evaluation assess the perceptual quality of the video. For a medical video, assessing quality in terms of “diagnostic” value rather than “perceptual” quality is more important. We present a diagnostic-quality–oriented video quality metric for quality evaluation of cardiac ultrasound videos. Cardiac ultrasound videos are characterized by rapid repetitive cardiac motions and distinct structural information characteristics that are explored by the proposed metric. Cardiac ultrasound video quality index, the proposed metric, is a full reference metric and uses the motion and edge information of the cardiac ultrasound video to evaluate the video quality. The metric was evaluated for its performance in approximating the quality of cardiac ultrasound videos by testing its correlation with the subjective scores of medical experts. The results of our tests showed that the metric has high correlation with medical expert opinions and in several cases outperforms the state-of-the-art video quality metrics considered in our tests. PMID:27014715

The identification of clinically important elements within medical journal abstracts: Patient-Population-Problem, Exposure-Intervention, Comparison, Outcome, Duration and Results (PECODR).

PubMed

Dawes, Martin; Pluye, Pierre; Shea, Laura; Grad, Roland; Greenberg, Arlene; Nie, Jian-Yun

2007-01-01

Information retrieval in primary care is becoming more difficult as the volume of medical information held in electronic databases expands. The lexical structure of this information might permit automatic indexing and improved retrieval. To determine the possibility of identifying the key elements of clinical studies, namely Patient-Population-Problem, Exposure-Intervention, Comparison, Outcome, Duration and Results (PECODR), from abstracts of medical journals. We used a convenience sample of 20 synopses from the journal Evidence-Based Medicine (EBM) and their matching original journal article abstracts obtained from PubMed. Three independent primary care professionals identified PECODR-related extracts of text. Rules were developed to define each PECODR element and the selection process of characters, words, phrases and sentences. From the extracts of text related to PECODR elements, potential lexical patterns that might help identify those elements were proposed and assessed using NVivo software. A total of 835 PECODR-related text extracts containing 41,263 individual text characters were identified from 20 EBM journal synopses. There were 759 extracts in the corresponding PubMed abstracts containing 31,947 characters. PECODR elements were found in nearly all abstracts and synopses with the exception of duration. There was agreement on 86.6% of the extracts from the 20 EBM synopses and 85.0% on the corresponding PubMed abstracts. After consensus this rose to 98.4% and 96.9% respectively. We found potential text patterns in the Comparison, Outcome and Results elements of both EBM synopses and PubMed abstracts. Some phrases and words are used frequently and are specific for these elements in both synopses and abstracts. Results suggest a PECODR-related structure exists in medical abstracts and that there might be lexical patterns specific to these elements. More sophisticated computer-assisted lexical-semantic analysis might refine these results, and pave the way

Automatic indexing of scanned documents: a layout-based approach

NASA Astrophysics Data System (ADS)

Esser, Daniel; Schuster, Daniel; Muthmann, Klemens; Berger, Michael; Schill, Alexander

2012-01-01

Archiving official written documents such as invoices, reminders and account statements in business and private area gets more and more important. Creating appropriate index entries for document archives like sender's name, creation date or document number is a tedious manual work. We present a novel approach to handle automatic indexing of documents based on generic positional extraction of index terms. For this purpose we apply the knowledge of document templates stored in a common full text search index to find index positions that were successfully extracted in the past.

Full Text Journal Subscriptions: An Evolutionary Process.

ERIC Educational Resources Information Center

Luther, Judy

1997-01-01

Provides an overview of companies offering Web accessible subscriptions to full text electronic versions of scientific, technical, and medical journals (Academic Press, Blackwell, EBSCO, Elsevier, Highwire Press, Information Quest, Institute of Physics, Johns Hopkins University Press, OCLC, OVID, Springer, and SWETS). Also lists guidelines for…

Mapping the literature of medical-surgical nursing.

PubMed

Taylor, Mary K

2006-04-01

Medical-surgical or adult health nursing is a complex specialty that requires a wide-ranging literature to inform its research and practice. Several excellent qualitative aids exist for collection development for this field, but quantitative studies are few. While one bibliometric study of journals exists, no recent work had been done in this area. The Mapping the Literature of Nursing Project protocol was used. Four source journals were selected, and a citation analysis of articles from 1996 to 1998 was conducted. A list of the most frequently cited journals was created, using Bradford's Law of Scattering. The list demonstrates that 1.2% of the cited medical-surgical nursing journals produced just over 33% of the citations. PubMed/MEDLINE, CINAHL, and Science Citation Index provided the most complete indexing coverage of all of the journals, with CINAHL providing the most complete coverage of nursing journals. Books were the second-most cited format. Citation analysis of journal articles is a useful aid for selecting journals for medical-surgical nursing collections, but it did not prove to be as useful for selecting materials in other formats. Indexes in addition to PubMed/MEDLINE are necessary to provide access to the journal literature serving this specialty.

Inflation in DoD Medical Care.

DTIC Science & Technology

1997-07-01

cataract surgery , to the outpatient setting); • 1.4%, trends in medical practice in place prior to PPS; • 0.0%, aging of the Medicare population...HFCA’s Medicare Economic Index.17 The MEI is used to update payments for physician services under Medicare Part B. The MEI is oriented toward care... physician services industry.l% [emphasis added] Table III-3. Medicare Economic Index: Expense Categories, Expenditure Weights, and Price Proxies

Intervention to enhance communication about newly prescribed medications.

PubMed

Tarn, Derjung M; Paterniti, Debora A; Orosz, Deborah K; Tseng, Chi-Hong; Wenger, Neil S

2013-01-01

Physicians prescribing new medications often do not convey important medication-related information. This study tests an intervention to improve physician-patient communication about newly prescribed medications. We conducted a controlled clinical trial of patients in 3 primary care practices, combining data from patient surveys with audio-recorded physician-patient interactions. The intervention consisted of a 1-hour physician-targeted interactive educational session encouraging communication about 5 basic elements regarding a new prescription and a patient information handout listing the 5 basic elements. Main outcome measures were the Medication Communication Index (MCI), a 5-point index assessed by qualitative analysis of audio-recorded interactions (giving points for discussion of medication name, purpose, directions for use, duration of use, and side effects), and patient ratings of physician communication about new prescriptions. Twenty-seven physicians prescribed 113 new medications to 82 of 256 patients. The mean MCI for medications prescribed by physicians in the intervention group was 3.95 (SD = 1.02), significantly higher than that for medications prescribed by control group physicians (2.86, SD = 1.23, P <.001). This effect held regardless of medication type (chronic vs nonchronic medication). Counseling about 3 of the 5 MCI components was significantly higher for medications prescribed by physicians in the intervention group, as were patients' ratings of new medication information transfer (P = .02). Independent of intervention or control groups, higher MCI scores were associated with better patient ratings about information about new prescriptions (P = .003). A physician-targeted educational session improved the content of and enhanced patient ratings of physician communication about new medication prescriptions. Further work is required to assess whether improved communication stimulated by the intervention translates into better clinical outcomes.

Etiology of Readmissions Following Orthopaedic Procedures and Medical Admissions. A Comparative Analysis.

PubMed

Maslow, Jed; Hutzler, Lorraine; Slover, James; Bosco, Joseph

2015-12-01

The Federal Government, the largest payer of health care, considers readmission within 30 days of discharge an indicator of quality of care. Many studies have focused on causes for and strategies to reduce readmissions following medical admissions. However, few studies have focused on the differences between them. We believe that the causes for readmission following orthopaedic surgery are markedly different than those following medical admissions, and therefore, the strategies developed to reduce medical readmissions will not be as effective in reducing readmissions after elective orthopaedic surgery. All unplanned 30-day readmissions following an index hospitalization for an elective orthopaedic procedure (primary and revision total joint arthroplasty and spine procedure) or for one of the three publicly reported medical conditions (AMI, HF, and pneumonia, which accounted for 11% of readmissions) were identified at our institution from 2010 through 2012. A total of 268 patients and 390 medical patients were identified as having an unplanned 30-day readmission. We reviewed a prospectively collected data base to determine the reason for readmission in each encounter. A total of 233 (86.9%) orthopaedic patients were readmitted for surgical complications, most commonly for a wound infection (56.0%) or wound complication (11.6%). Following an index admission of HF or AMI, the primary reason for readmission was a disease of the circulatory system (55.9% and 57.4%, respectively). Following an index admission for pneumonia, the primary reason for readmission was a disease of the respiratory system (34.5%). The causes of readmissions following orthopaedic surgery and medical admissions are different. Patients undergoing orthopaedic procedures are readmitted for surgical complications, frequently unrelated to aftercare, and medicine patients are readmitted for reasons related to the index diagnosis. Interventions designed to reduce orthopaedic readmissions must focus on

Medication Guide

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Healthcare resource utilisation by patients with coronary heart disease receiving a lifestyle-focused text message support program: an analysis from the TEXT ME study.

PubMed

Thakkar, Jay; Redfern, Julie; Khan, Ehsan; Atkins, Emily; Ha, Jeffrey; Vo, Kha; Thiagalingam, Aravinda; Chow, Clara K

2018-05-23

The 'Tobacco, Exercise and Diet Messages' (TEXT ME) study was a 6-month, single-centre randomised clinical trial (RCT) that found a text message support program improved levels of cardiovascular risk factors in patients with coronary heart disease (CHD). The current analyses examined whether receipt of text messages influenced participants' engagement with conventional healthcare resources. The TEXT ME study database (N=710) was linked with routinely collected health department databases. Number of doctor consultations, investigations and cardiac medication prescriptions in the two study groups were compared. The most frequently accessed health service was consultations with a General Practitioner (mean 7.1, s.d. 5.4). The numbers of medical consultations, biochemical tests or cardiac-specific investigations were similar between the study groups. There was at least one prescription registered for statin, ACEI/ARBs and β-blockers in 79, 66 and 50% of patients respectively, with similar refill rates in both the study groups. The study identified TEXT ME text messaging program did not increase use of Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) captured healthcare services. The observed benefits of TEXT ME reflect direct effects of intervention independent of conventional healthcare resource engagement.

Measuring effectiveness of electronic medical records systems: towards building a composite index for benchmarking hospitals.

PubMed

Otieno, George Ochieng; Hinako, Toyama; Motohiro, Asonuma; Daisuke, Koide; Keiko, Naitoh

2008-10-01

Many hospitals are currently in the process of developing and implementing electronic medical records (EMR) systems. This is a critical time for developing a framework that can measure and allow for comparison the effectiveness of EMR systems across hospitals that have implemented these systems. The motivation for this study comes from the realization that there is limited research on the understanding of the effectiveness of EMR systems, and a lack of appropriate reference theoretical framework for measuring the effectiveness of EMR systems. In this paper, we propose a conceptual framework for generating a composite index (CI) for measuring the effectiveness of EMR systems in hospitals. Data used to test the framework and associated research objectives were derived from a cross-sectional survey of five stakeholders of EMR systems including chief medical officers, chief nursing officers, chief information officers, doctors and nurses in 20 Japanese hospitals. Using statistical means of standardization and principal component analysis (PCA) procedure, CI was developed by summing up the scores of four dimensions-system quality, information quality, use and user satisfaction. The process included formulating items for each dimension, condensing the data into factors relevant to the dimension and calculating the CI by summing up the product of each dimension with its respective principal component score coefficient. The Cronbach's alpha for the four dimensions used in developing CI was .843. Validation of CI revealed that it was correlated to internal dimensions (system quality, R=.828; information quality, R=.909; use, R=.969; and user satisfaction, R=.679) and to external factors (JAHIS level, R=.832 and patient safety culture, R=.585). These results suggest that CI could be a reliable and valid measure of the effectiveness of EMR systems in the responding hospitals. On benchmarking of hospitals, 30.0% (6/20) of the responding hospitals performed less than

Using clinician text notes in electronic medical record data to validate transgender-related diagnosis codes.

PubMed

Blosnich, John R; Cashy, John; Gordon, Adam J; Shipherd, Jillian C; Kauth, Michael R; Brown, George R; Fine, Michael J

2018-04-04

Transgender individuals are vulnerable to negative health risks and outcomes, but research remains limited because data sources, such as electronic medical records (EMRs), lack standardized collection of gender identity information. Most EMR do not include the gold standard of self-identified gender identity, but International Classification of Diseases (ICDs) includes diagnostic codes indicating transgender-related clinical services. However, it is unclear if these codes can indicate transgender status. The objective of this study was to determine the extent to which patients' clinician notes in EMR contained transgender-related terms that could corroborate ICD-coded transgender identity. Data are from the US Department of Veterans Affairs Corporate Data Warehouse. Transgender patients were defined by the presence of ICD9 and ICD10 codes associated with transgender-related clinical services, and a 3:1 comparison group of nontransgender patients was drawn. Patients' clinician text notes were extracted and searched for transgender-related words and phrases. Among 7560 patients defined as transgender based on ICD codes, the search algorithm identified 6753 (89.3%) with transgender-related terms. Among 22 072 patients defined as nontransgender without ICD codes, 246 (1.1%) had transgender-related terms; after review, 11 patients were identified as transgender, suggesting a 0.05% false negative rate. Using ICD-defined transgender status can facilitate health services research when self-identified gender identity data are not available in EMR.

Frontiers of biomedical text mining: current progress

PubMed Central

Zweigenbaum, Pierre; Demner-Fushman, Dina; Yu, Hong; Cohen, Kevin B.

2008-01-01

It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or ‘BioNLP’ in general, focusing primarily on papers published within the past year. PMID:17977867

Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach.

PubMed

Oyehan, Tajudeen A; Alade, Ibrahim O; Bagudu, Aliyu; Sulaiman, Kazeem O; Olatunji, Sunday O; Saleh, Tawfik A

2018-04-30

The optical properties of blood play crucial roles in medical diagnostics and treatment, and in the design of new medical devices. Haemoglobin is a vital constituent of the blood whose optical properties affect all of the optical properties of human blood. The refractive index of haemoglobin has been reported to strongly depend on its concentration which is a function of the physiology of biological cells. This makes the refractive index of haemoglobin an essential non-invasive bio-marker of diseases. Unfortunately, the complexity of blood tissue makes it challenging to experimentally measure the refractive index of haemoglobin. While a few studies have reported on the refractive index of haemoglobin, there is no solid consensus with the data obtained due to different measuring instruments and the conditions of the experiments. Moreover, obtaining the refractive index via an experimental approach is quite laborious. In this work, an accurate, fast and relatively convenient strategy to estimate the refractive index of haemoglobin is reported. Thus, the GA-SVR model is presented for the prediction of the refractive index of haemoglobin using wavelength, temperature, and the concentration of haemoglobin as descriptors. The model developed is characterised by an excellent accuracy and very low error estimates. The correlation coefficients obtained in these studies are 99.94% and 99.91% for the training and testing results, respectively. In addition, the result shows an almost perfect match with the experimental data and also demonstrates significant improvement over a recent mathematical model available in the literature. The GA-SVR model predictions also give insights into the influence of concentration, wavelength, and temperature on the RI measurement values. The model outcome can be used not only to accurately estimate the refractive index of haemoglobin but also could provide a reliable common ground to benchmark the experimental refractive index results

The refractive index of human hemoglobin in the visible range.

PubMed

Zhernovaya, O; Sydoruk, O; Tuchin, V; Douplik, A

2011-07-07

Because the refractive index of hemoglobin in the visible range is sensitive to the hemoglobin concentration, optical investigations of hemoglobin are important for medical diagnostics and treatment. Direct measurements of the refractive index are, however, challenging; few such measurements have previously been reported, especially in a wide wavelength range. We directly measured the refractive index of human deoxygenated and oxygenated hemoglobin for nine wavelengths between 400 and 700 nm for the hemoglobin concentrations up to 140 g l(-1). This paper analyzes the results and suggests a set of model functions to calculate the refractive index depending on the concentration. At all wavelengths, the measured values of the refractive index depended on the concentration linearly. Analyzing the slope of the lines, we determined the specific refraction increments, derived a set of model functions for the refractive index depending on the concentration, and compared our results with those available in the literature. Based on the model functions, we further calculated the refractive index at the physiological concentration within the erythrocytes of 320 g l(-1). The results can be used to calculate the refractive index in the visible range for arbitrary concentrations provided that the refractive indices depend on the concentration linearly.

Use of electronic health record structured text and its payoffs. The approach and barriers to using structured text in EHR to document care encounters.

PubMed

Benge, James; Beach, Thomas; Gladding, Connie; Maestas, Gail

2008-01-01

The Military Health System (MHS) deployed its electronic health record (EHR), AHLTA to Military Treatment Facilities (MTFs) around the world. This paper focuses on the approach and barriers to using structured text in AHLTA to document care encounters and illustrates the direct correlation between the use of structured text and achievement of expected benefits. AHLTA uses commercially available products, a health data dictionary and standardized medical terminology, enabling the capture of structured computable data. With structured text stored in the AHLTA Clinical Data Repository (CDR), the MHS has seen a return on its EHR investment with improvements in the accuracy and completeness of coding and the documentation of care provided. Determining the aspects of documentation where structured text is most beneficial, as well as the degree of structured text needed has been a significant challenge. This paper describes how the economic value framework aligns the enterprise strategic objectives with the EHR investment features, performance metrics and expected benefits. The framework analyses focus on return on investment calculations, baseline assessment and post-implementation benefits validation. Cost avoidance, revenue enhancements and operational improvements, such as evidence-based medicine and medical surveillance can be directly attributed to use structured text.

Pain and suffering disability index.

PubMed

Brown, Melissa M; Brown, Gary C; Brown, Heidi; Sharma, Sanjay; Wagner, Thomas; Kraushar, Marvin

2006-06-01

This report summarizes the increasing financial resources required to deal with personal injury tort cases and medical malpractice. The largest single component in personal injury torts is noneconomic damages, which encompasses 'pain and suffering' and punitive damage, the latter of which comprises only a small percentage. Overall, noneconomic damages account for 24% of the greater than US$250 billion spent annually on personal injury torts. A pain and suffering disability index has been developed that quantifies the loss of life's value attributable to personal injury. Based upon time-tradeoff utility analysis, the value loss is predicated upon the values of people who have experienced the same degree of disability or injury as the plaintiff, only outside the courtroom environs. It is believed that the pain and suffering disability index will readily identify frivolous, personal injury torts, decrease the number of frivolous, personal injury torts, markedly decrease the variance of noneconomic tort settlements, facilitate the earlier settlement of personal injury tort cases, and decrease the proportion of personal injury tort cases progressing to jury trial. The pain and suffering disability index is a novel instrument that quantifies the 'pain and suffering' associated with a personal injury tort according to the values of patients who have experienced a similar injury outside the courtroom environs.

Mobile phone text messaging interventions for HIV and other chronic diseases: an overview of systematic reviews and framework for evidence transfer.

PubMed

Mbuagbaw, Lawrence; Mursleen, Sara; Lytvyn, Lyubov; Smieja, Marek; Dolovich, Lisa; Thabane, Lehana

2015-01-22

Strong international commitment and the widespread use of antiretroviral therapy have led to higher longevity for people living with human immune deficiency virus (HIV). Text messaging interventions have been shown to improve health outcomes in people living with HIV. The objectives of this overview were to: map the state of the evidence of text messaging interventions, identify knowledge gaps, and develop a framework for the transfer of evidence to other chronic diseases. We conducted a systematic review of systematic reviews on text messaging interventions to improve health or health related outcomes. We conducted a comprehensive search of PubMed, EMBASE (Exerpta Medica Database), CINAHL (Cumulative Index to Nursing and Allied Health Literature), PsycINFO, Web of Science (WoS) and the Cochrane Library on the 17th April 2014. Screening, data extraction and assessment of methodological quality were done in duplicate. Our findings were used to develop a conceptual framework for transfer. Our search identified 135 potential systematic reviews of which nine were included, reporting on 37 source studies, conducted in 19 different countries. Seven of nine (77.7%) of these reviews were high quality. There was some evidence for text messaging as a tool to improve adherence to antiretroviral therapy. Text messages also improved attendance at appointments and behaviour change outcomes. The findings were inconclusive for self-management of illness, treatment of tuberculosis and communicating results of medical investigations. The geographical distribution of text messaging research was limited to specific regions of the world. Prominent knowledge gaps included the absence of data on long term outcomes, patient satisfaction, and economic evaluations. The included reviews also identified methodological limitations in many of the primary studies. Global evidence supports the use of text messaging as a tool to improve adherence to medication and attendance at scheduled

Change In Length of Stay and Readmissions among Hospitalized Medical Patients after Inpatient Medicine Service Adoption of Mobile Secure Text Messaging.

PubMed

Patel, Mitesh S; Patel, Neha; Small, Dylan S; Rosin, Roy; Rohrbach, Jeffrey I; Stromberg, Nathaniel; Hanson, C William; Asch, David A

2016-08-01

Changes in the medium of communication from paging to mobile secure text messaging may change clinical care, but the effects of these changes on patient outcomes have not been well examined. To evaluate the association between inpatient medicine service adoption of mobile secure text messaging and patient length of stay and readmissions. Observational study. Patients admitted to medicine services at the Hospital of the University of Pennsylvania (intervention site; n = 8995 admissions of 6484 patients) and Penn Presbyterian Medical Center (control site; n = 6799 admissions of 4977 patients) between May 1, 2012, and April 30, 2014. Mobile secure text messaging. Change in length of stay and 30-day readmissions, comparing patients at the intervention site to the control site before (May 1, 2012 to April 30, 2013) and after (May 1, 2013 to April 30, 2014) the intervention, adjusting for time trends and patient demographics, comorbidities, insurance, and disposition. During the pre-intervention period, the mean length of stay ranged from 4.0 to 5.0 days at the control site and from 5.2 to 6.7 days at the intervention site, but trends were similar. In the first month after the intervention, the mean length of stay was unchanged at the control site (4.7 to 4.7 days) but declined at the intervention site (6.0 to 5.4 days). Trends were mostly similar during the rest of the post-intervention period, ranging from 4.4 to 5.6 days at the control site and from 5.4 to 6.5 days at the intervention site. Readmission rates varied significantly within sites before and after the intervention, but overall trends were similar. In adjusted analyses, there was a significant decrease in length of stay for the intervention site relative to the control site during the post-intervention period compared to the pre-intervention period (-0.77 days ; 95 % CI, -1.14, -0.40; P < 0.001). There was no significant difference in the odds of readmission (OR, 0.97; 95 % CI: 0.81, 1.17; P�

Fire technology abstracts, volume 4. Cumulative indexes

NASA Astrophysics Data System (ADS)

1982-03-01

Cumulative subject, author, publisher, and report number indexes referencing articles, books, reports, and patents are provided. The dynamics of fire, behavior and properties of materials, fire modeling and test burns, fire protection, fire safety, fire service organization, apparatus and equipment, fire prevention suppression, planning, human behavior, medical problems, codes and standards, hazard identification, safe handling of materials, and insurance economics of loss and prevention are among the subjects covered.

Short Text Messages to Encourage Adherence to Medication and Follow-up for People With Psychosis (Mobile.Net): Randomized Controlled Trial in Finland.

PubMed

Välimäki, Maritta; Kannisto, Kati Anneli; Vahlberg, Tero; Hätönen, Heli; Adams, Clive E

2017-07-12

A text messaging service (short message service [SMS]) has the potential to target large groups of people with long-term illnesses such as serious mental disorders, who may have difficulty with treatment adherence. Robust research on the impact of mobile technology interventions for these patients remains scarce. The main objective of our study was to investigate the impact of individually tailored short text messages on the rate of psychiatric hospital readmissions, health care service use, and clinical outcomes. In addition, we analyzed treatment costs. Between September 2011 and November 2012, we randomly assigned 1139 people to a tailored text message intervention (n=569) or usual care (n=570). Participants received semiautomated text messages for up to 12 months or usual care. The primary outcome, based on routinely collected health register data, was patient readmission into a psychiatric hospital during a 12-month follow-up period. Secondary outcomes were related to other service use, coercion, medication, adverse events, satisfaction, social functioning, quality of life, and economic factors (cost analysis). There was 98.24% (1119/1139) follow-up at 12 months. Tailored mobile telephone text messages did not reduce the rate of hospital admissions (242/563, 43.0% of the SMS group vs 216/556, 38.8% of the control group; relative risk 1.11; 95% CI 0.92-1.33; P=.28), time between hospitalizations (mean difference 7.0 days 95% CI -8.0 to 24.0; P=.37), time spent in a psychiatric hospital during the year (mean difference 2.0 days 95% CI -2.0 to 7.0; P=.35), or other service outcomes. People who received text messages were less disabled, based on Global Assessment Scale scores at the time of their readmission, than those who did not receive text messages (odds ratio 0.68; 95% CI 0.47-0.97; P=.04). The costs of treatment were higher for people in the SMS group than in the control group (mean €10,103 vs €9210, respectively, P<.001). High-grade routinely collected

Social science and linguistic text analysis of nurses' records: a systematic review and critique.

PubMed

Buus, Niels; Hamilton, Bridget Elizabeth

2016-03-01

The two aims of the paper were to systematically review and critique social science and linguistic text analyses of nursing records in order to inform future research in this emerging area of research. Systematic searches in reference databases and in citation indexes identified 12 articles that included analyses of the social and linguistic features of records and recording. Two reviewers extracted data using established criteria for the evaluation of qualitative research papers. A common characteristic of nursing records was the economical use of language with local meanings that conveyed little information to the uninitiated reader. Records were dominated by technocratic-medical discourse focused on patients' bodies, and they depicted only very limited aspects of nursing practice. Nurses made moral evaluations in their categorisation of patients, which reflected detailed surveillance of patients' disturbing behaviour. The text analysis methods were rarely transparent in the articles, which could suggest research quality problems. For most articles, the significance of the findings was substantiated more by theoretical readings of the institutional settings than by the analysis of textual data. More probing empirical research of nurses' records and a wider range of theoretical perspectives has the potential to expose the situated meanings of nursing work in healthcare organisations. © 2015 John Wiley & Sons Ltd.

Neural activity tied to reading predicts individual differences in extended-text comprehension

PubMed Central

Mossbridge, Julia A.; Grabowecky, Marcia; Paller, Ken A.; Suzuki, Satoru

2013-01-01

Reading comprehension depends on neural processes supporting the access, understanding, and storage of words over time. Examinations of the neural activity correlated with reading have contributed to our understanding of reading comprehension, especially for the comprehension of sentences and short passages. However, the neural activity associated with comprehending an extended text is not well-understood. Here we describe a current-source-density (CSD) index that predicts individual differences in the comprehension of an extended text. The index is the difference in CSD-transformed event-related potentials (ERPs) to a target word between two conditions: a comprehension condition with words from a story presented in their original order, and a scrambled condition with the same words presented in a randomized order. In both conditions participants responded to the target word, and in the comprehension condition they also tried to follow the story in preparation for a comprehension test. We reasoned that the spatiotemporal pattern of difference-CSDs would reflect comprehension-related processes beyond word-level processing. We used a pattern-classification method to identify the component of the difference-CSDs that accurately (88%) discriminated good from poor comprehenders. The critical CSD index was focused at a frontal-midline scalp site, occurred 400–500 ms after target-word onset, and was strongly correlated with comprehension performance. Behavioral data indicated that group differences in effort or motor preparation could not explain these results. Further, our CSD index appears to be distinct from the well-known P300 and N400 components, and CSD transformation seems to be crucial for distinguishing good from poor comprehenders using our experimental paradigm. Once our CSD index is fully characterized, this neural signature of individual differences in extended-text comprehension may aid the diagnosis and remediation of reading comprehension deficits. PMID

Decreasing the load? Is a Multidisciplinary Multistep Medication Review in older people an effective intervention to reduce a patient's Drug Burden Index? Protocol of a randomised controlled trial.

PubMed

van der Meer, Helene G; Wouters, Hans; van Hulten, Rolf; Pras, Niesko; Taxis, Katja

2015-12-23

Older people often use medications with anticholinergic or sedative side effects which increase the risk of falling and worsen cognitive impairment. The Drug Burden Index (DBI) is a measure of the burden of anticholinergic and sedative medications. Medication reviews are typically done by a pharmacist in collaboration with a general practitioner to optimise the medication use and reduce these adverse drug events. We will evaluate whether a Multidisciplinary Multistep Medication Review (3MR) is an effective intervention to reduce a patient's DBI. A randomised controlled trial including 160 patients from 15 community pharmacies will be conducted. Per pharmacy, 1 pharmacist will perform a structured 3MR in close collaboration with the general practitioner, including the objective to reduce the DBI. Primary outcome--the difference in proportion of patients having a decrease in DBI ≥ 0.5 in the intervention and control groups at follow-up. Secondary outcomes--anticholinergic and sedative side effects, falls, cognitive function, activities of daily living, quality of life, hospital admission, and mortality. The burden of patients will be kept at a minimum. The 3MR can be considered as usual care by the pharmacist and general practitioner. Medical specialists will be consulted, if necessary. The intervention is specifically aimed at older community-dwelling patients in an attempt to optimise prescribing, in particular, to reduce medication with anticholinergic and sedative properties. Study results will be published in peer-reviewed journals and will be distributed through information channels targeting professionals. NCT02317666; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Patients’ perspectives on the medical primary–secondary care interface: systematic review and synthesis of qualitative research

PubMed Central

Sampson, Rod; Cooper, Jamie; Barbour, Rosaline; Polson, Rob; Wilson, Philip

2015-01-01

Objectives To synthesise the published literature on the patient experience of the medical primary–secondary care interface and to determine priorities for future work in this field aimed at improving clinical outcomes. Design Systematic review and metaethnographic synthesis of primary studies that used qualitative methods to explore patients’ perspectives of the medical primary–secondary care interface. Setting International primary–secondary care interface. Data sources EMBASE, MEDLINE, CINAHL Plus with Full text, PsycINFO, Psychology and Behavioural Sciences Collection, Health Business Elite, Biomedica Reference Collection: Comprehensive Library, Information Science & Technology Abstracts, eBook Collection, Web of Science Core Collection: Citation Indexes and Social Sciences Citation Index, and grey literature. Eligibility criteria for selecting studies Studies were eligible for inclusion if they were full research papers employing qualitative methodology to explore patients’ perspectives of the medical primary–secondary care interface. Review methods The 7-step metaethnographic approach described by Noblit and Hare, which involves cross-interpretation between studies while preserving the context of the primary data. Results The search identified 690 articles, of which 39 were selected for full-text review. 20 articles were included in the systematic review that encompassed a total of 689 patients from 10 countries. 4 important areas specific to the primary–secondary care interface from the patients’ perspective emerged: barriers to care, communication, coordination, and ‘relationships and personal value’. Conclusions and implications of key findings Patients should be the focus of any transfer of care between primary and secondary systems. From their perspective, areas for improvement may be classified into four domains that should usefully guide future work aimed at improving quality at this important interface. Trial registration number

Representing nested semantic information in a linear string of text using XML.

PubMed

Krauthammer, Michael; Johnson, Stephen B; Hripcsak, George; Campbell, David A; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information.

Representing nested semantic information in a linear string of text using XML.

PubMed Central

Krauthammer, Michael; Johnson, Stephen B.; Hripcsak, George; Campbell, David A.; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information. PMID:12463856

Analysis of semantic search within the domains of uncertainty: using Keyword Effectiveness Indexing as an evaluation tool.

PubMed

Lorence, Daniel; Abraham, Joanna

2006-01-01

Medical and health-related searches pose a special case of risk when using the web as an information resource. Uninsured consumers, lacking access to a trained provider, will often rely on information from the internet for self-diagnosis and treatment. In areas where treatments are uncertain or controversial, most consumers lack the knowledge to make an informed decision. This exploratory technology assessment examines the use of Keyword Effectiveness Indexing (KEI) analysis as a potential tool for profiling information search and keyword retrieval patterns. Results demonstrate that the KEI methodology can be useful in identifying e-health search patterns, but is limited by semantic or text-based web environments.

Scientific production of medical sciences universities in north of iran.

PubMed

Siamian, Hasan; Firooz, Mousa Yamin; Vahedi, Mohammad; Aligolbandi, Kobra

2013-01-01

NONE DECLARED. The study of the scientific evidence citation production by famous databases of the world is one of the important indicators to evaluate and rank the universities. The study at investigating the scientific production of Northern Iran Medical Sciences Universities in Scopus from 2005 through 2010. This survey used scientometrics technique. The samples under studies were the scientific products of four northern Iran Medical universities. Viewpoints quantity of the Scientific Products Mazandaran University of Medical Sciences stands first and of Babol University of Medical Sciences ranks the end, but from the viewpoints of quality of scientific products of considering the H-Index and the number of cited papers the Mazandaran University of Medical Sciences is a head from the other universities under study. From the viewpoints of subject of the papers, the highest scientific products belonged to the faculty of Pharmacy affiliated to Mazandaran University of Medial Sciences, but the three other universities for the genetics and biochemistry. Results showed that the Mazandaran University of Medical Sciences as compared to the other understudies universities ranks higher for the number of articles, cited articles, number of hard work authors and H-Index of Scopus database from 2005 through 2010.

[Modification and evaluation of assessment of 
medication literacy].

PubMed

Zheng, Feng; Zhong, Zhuqing; Ding, Siqing; Luo, Aijing; Liu, Zina

2016-11-28

To translate and revise the Medication Literacy Assessment in English (MedLitRxSE-English) and evaluate its validity and reliability.
 Methods: We introduced MedLitRxSE-English from abroad. According to the principles of Brislin and culture adjustment, we revised it as a Chinese edition. Using random sampling method, from Oct, 2014 to Jan, 2015, 461 non-hospitalized patients from the outpatient departments of the top three hospitals in Changsha city were investigated. The reliability and validity of the scale was tested.
 Results: The test-retest reliability of the Chinese version for medication literacy scale was 0.885; the split reliability was 0.840; K-R was 0.820; the correlations between the assessment of medication literacy and the corresponding items were 0.427-0.587; the confirmatory factor analysis revealed overall good fit. Root mean square error of approximation (RMSEA), χ2/df, goodness of fit index (GFI) and comparative fit index (CFI) was 0.08, 3.06, 0.91 and 0.94, respectively. 
 Conclusion: The Chinese version for the assessment of medication literacy is in good reliability and validity, and it can be used to evaluate the medication literacy in our country.

AAPM medical physics practice guideline 6.a.: Performance characteristics of radiation dose index monitoring systems.

PubMed

Gress, Dustin A; Dickinson, Renee L; Erwin, William D; Jordan, David W; Kobistek, Robert J; Stevens, Donna M; Supanich, Mark P; Wang, Jia; Fairobent, Lynne A

2017-07-01

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education and professional practice of medical physics. The AAPM has more than 8,000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: •Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. •Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

How to Use Current Medical Literature and APA Format Style.

ERIC Educational Resources Information Center

Peek, Robin

Directives and guidance in obtaining current medical literature are provided in this publication with special emphasis given to locating material in the Portland, Oregon area. The uses and types of periodical indexes are identified and periodical index citation examples are indicated. Explanations are offered on: (1) how to conduct an effective…

Econo-ESA in semantic text similarity.

PubMed

Rahutomo, Faisal; Aritsugi, Masayoshi

2014-01-01

Explicit semantic analysis (ESA) utilizes an immense Wikipedia index matrix in its interpreter part. This part of the analysis multiplies a large matrix by a term vector to produce a high-dimensional concept vector. A similarity measurement between two texts is performed between two concept vectors with numerous dimensions. The cost is expensive in both interpretation and similarity measurement steps. This paper proposes an economic scheme of ESA, named econo-ESA. We investigate two aspects of this proposal: dimensional reduction and experiments with various data. We use eight recycling test collections in semantic text similarity. The experimental results show that both the dimensional reduction and test collection characteristics can influence the results. They also show that an appropriate concept reduction of econo-ESA can decrease the cost with minor differences in the results from the original ESA.

Inductive creation of an annotation schema for manually indexing clinical conditions from emergency department reports

PubMed Central

Chapman, Wendy W.; Dowling, John N.

2006-01-01

Evaluating automated indexing applications requires comparing automatically indexed terms against manual reference standard annotations. However, there are no standard guidelines for determining which words from a textual document to include in manual annotations, and the vague task can result in substantial variation among manual indexers. We applied grounded theory to emergency department reports to create an annotation schema representing syntactic and semantic variables that could be annotated when indexing clinical conditions. We describe the annotation schema, which includes variables representing medical concepts (e.g., symptom, demographics), linguistic form (e.g., noun, adjective), and modifier types (e.g., anatomic location, severity). We measured the schema’s quality and found: (1) the schema was comprehensive enough to be applied to 20 unseen reports without changes to the schema; (2) agreement between author annotators applying the schema was high, with an F measure of 93%; and (3) an error analysis showed that the authors made complementary errors when applying the schema, demonstrating that the schema incorporates both linguistic and medical expertise. PMID:16230050

Effects of Picture Labeling on Science Text Processing and Learning: Evidence from Eye Movements

ERIC Educational Resources Information Center

Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina

2013-01-01

This study investigated the effects of reading a science text illustrated by either a labeled or unlabeled picture. Both the online process of reading the text and the offline conceptual learning from the text were examined. Eye-tracking methodology was used to trace text and picture processing through indexes of first- and second-pass reading or…

Automatic NEPHIS Coding of Descriptive Titles for Permuted Index Generation.

ERIC Educational Resources Information Center

Craven, Timothy C.

1982-01-01

Describes a system for the automatic coding of most descriptive titles which generates Nested Phrase Indexing System (NEPHIS) input strings of sufficient quality for permuted index production. A series of examples and an 11-item reference list accompany the text. (JL)

Use of speech-to-text technology for documentation by healthcare providers.

PubMed

Ajami, Sima

2016-01-01

Medical records are a critical component of a patient's treatment. However, documentation of patient-related information is considered a secondary activity in the provision of healthcare services, often leading to incomplete medical records and patient data of low quality. Advances in information technology (IT) in the health system and registration of information in electronic health records (EHR) using speechto- text conversion software have facilitated service delivery. This narrative review is a literature search with the help of libraries, books, conference proceedings, databases of Science Direct, PubMed, Proquest, Springer, SID (Scientific Information Database), and search engines such as Yahoo, and Google. I used the following keywords and their combinations: speech recognition, automatic report documentation, voice to text software, healthcare, information, and voice recognition. Due to lack of knowledge of other languages, I searched all texts in English or Persian with no time limits. Of a total of 70, only 42 articles were selected. Speech-to-text conversion technology offers opportunities to improve the documentation process of medical records, reduce cost and time of recording information, enhance the quality of documentation, improve the quality of services provided to patients, and support healthcare providers in legal matters. Healthcare providers should recognize the impact of this technology on service delivery.

Variations in contact patterns and dispatch guideline adherence between Norwegian emergency medical communication centres - a cross-sectional study

PubMed Central

2014-01-01

Background The 19 Norwegian Emergency medical communication centres (EMCCs) use Norwegian Index for medical emergency assistance (Index) as dispatch guidelines. Little is known about the use of Index, nor its validity. We aimed to document the epidemiology of contacts made to the public emergency medical phone number and the operators’ self-reported use of Index as a first step towards a validation study. Methods We registered all medical emergency calls to the EMCCs during a 72 h period in a national cross sectional study. We subsequently sent a questionnaire to all EMCC operators in Norway, asking how they use Index. A combined outcome variable “use of Index” was computed through a Likert scale, range 1–5. Regression models were used to examine factors influencing use. Results 2 298 contacts were included. National contact rate was 56/1 000 inhabitants per year, range between EMCCs 34 – 119. Acute contact (life-threatening situations) rate was 21/1 000 per year, range between EMCCs 5 – 31. Index criteria 6 – ’Unresolved problem’ accounts for 20% of the 113 contacts, range between EMCCs 10 – 42%. The mean use of Index was 3.95 (SD 0.39), corresponding to “more than 75% of emergency calls”. There were differences in use of Index on EMCC level, range 3.7 – 4.4, and a multi regression model explained 23.4% of the variation in use. Operators working rotation with ground ambulance services reported reduced use of Index compared to operators not working in rotation, while distinct EMCC focus on Index increased use of Index compared to EMCCs with no focus on Index. Use of electronic records and operators experience were the main reasons given for not using Index. Conclusions There is a large variation between the EMCCs with regard to both contact patterns and use of Index. There is a relatively high overall self-reported use of Index by the operators, with variations on both individual and EMCC level. PMID:24398290

Treating laryngopharyngeal reflux: Evaluation of an anti-reflux program with comparison to medications.

PubMed

Yang, Jin; Dehom, Salem; Sanders, Stephanie; Murry, Thomas; Krishna, Priya; Crawley, Brianna K

To determine if an anti-reflux induction program relieves laryngopharyngeal reflux (LPR) symptoms more effectively than medication and behavioral changes alone. Retrospective study. Tertiary care academic center. A database was populated with patients treated for LPR. Patients were included in the study group if they completed a two-week anti-reflux program (diet, alkaline water, medications, behavioral modifications). Patients were included in the control group if they completed anti-reflux medications and behavioral modifications only. Patients completed the voice handicap index (VHI), reflux symptom index (RSI), cough severity index (CSI), dyspnea index (DI) and eating assessment tool (EAT-10) surveys and underwent laryngoscopy for examination and reflux finding score (RFS) quantification. Of 105 study group patients, 96 (91%) reported subjective improvement in their LPR symptoms after an average 32-day first follow-up and their RSI and CSI scores improved significantly. No significant differences were found in VHI, DI, or EAT-10 scores. Fifteen study patients who had previously failed adequate high-dose medication trials reported improvement and their CSI and EAT-10 scores improved significantly. Ninety-five percent of patients with a chief complaint of cough reported improvement and their CSI scores improved significantly from 12.3 to 8.2. Among 81 controls, only 39 (48%) patients reported improvement after an average 62-day first follow-up. Their RSI scores did not significantly change. The anti-reflux program yielded rapid and substantial results for a large cohort of patients with LPR. It compared favorably with medication and behavioral modification alone. It was effective in improving cough and treating patients who had previously failed medications alone. Copyright © 2017 Elsevier Inc. All rights reserved.

The handsearching of 2 medical journals of Bahrain for reports of randomized controlled trials.

PubMed

Al-Hajeri, Amani A; Fedorowicz, Zbigniew; Amin, Fawzi A; Eisinga, Anne

2006-04-01

To identify reports of randomized trials by handsearching 2 Bahrain medical journals, which are indexed in the biomedical database EMBASE and to determine any added value of the handsearching by comparing the reports found by handsearching with what would have been found by searching EMBASE to examine (i) the precision and sensitivity of the EMBASE index term Randomized Controlled Trial (RCT) and (ii) The Cochrane Collaboration's systematic electronic search of EMBASE (which uses 4 index terms and 9 free-text terms). All issues of the Bahrain Medical Bulletin (BMB) (1979-2004) and the Journal of the Bahrain Medical Society (JBMS) (1989-2004) were handsearched in February 2005 for reports of RCTs or Controlled Clinical Trials (CCTs), according to Cochrane eligibility criteria. Out of 395 articles in BMB we found reports of 12 RCTs and 4 CCTs. Distribution by country of corresponding author: Jordan (4 RCTs, one CCT), Bahrain (one RCT, one CCT), India (3 RCTs, one CCT), Kuwait (one CCT), Saudi Arabia (2 RCTs), USA/Bahrain (one RCT), and Oman (one RCT); and by specialty: Anesthesia (8), Surgery (1) Pediatrics (1), Radiotherapy (1), Community Medicine (1), Sports Medicine (1), Obstetrics/Gynecology (3). The Journal of the Bahrain Medical Society included reports of 14 RCTs and 3 CCTs, out of 97 articles. Distribution by country of corresponding author: Jordan (9 RCTs, 2 CCTs), Bahrain (3 RCTs), Egypt (one RCT), Kuwait (one RCT), and Saudi Arabia (one RCT); and by specialty: Anesthesia (7), General Surgery (3), Obstetrics/Gynecology (1), Radiotherapy (1), Pediatrics (1), Orthopaedic Surgery (1), Education (1) Ear Nose and Throat (1) Ophthalmology (1). Overall, of the 33 reports of trials found by handsearching both journals, only 23 were included in EMBASE of which only 6 had been indexed with the term RCT. Of the 23 reports of trials included in EMBASE, 16 had been identified in the Collaboration s systematic search of EMBASE. Two reports of trials could have been

[Impact factor of the Spanish medical journals].

PubMed

Aleixandre Benavent, Rafael; Valderrama Zurián, Juan Carlos; Castellano Gómez, Miguel; Simó Meléndez, Raquel; Navarro Molina, Carolina

2004-11-20

The 2001 edition of the Journal Citation Reports (JCR) includes only 13 Spanish medical journals. The impact factor (IF) of the rest of Spanish medical journals is unknown. The aim of this study is to determine the IF of the main Spanish medical journals, taking also into account the references from journals not covered by the SCI. A set of 87 Spanish medical journals was selected from the national database IME and other international databases. All citable articles published in these journals in 2001 were analyzed, extracting their bibliographic references to articles published in 1999, 2000 and 2001. The indicators obtained for each journal were the number of cites, the IF and the immediacy index. Among the 87 source journals, 74 were not included in the JCR. From them, 5,388 bibliographic references were examined, identifying the journals cited. Final indicators were obtained adding these results to the ones obtained by using the Science Citation Index. The most cited journal was Medicina Clinica (768 cites), and the highest IF were attained by Histology and Histopathology (IF = 1.866), International Journal of Developmental Biology (IF = 1.654) and Medicina Clinica (IF = 1.125). This work has permitted to obtain the IF of 87 Spanish medical journals. Already detected in previous works, the leadership of the journal Medicina Clinica in Spanish medicine is confirmed. Spanish medical journals published in English have received a small number of cites from the ones published in Spanish. A low impact factor is not necessarily related to lack of quality, merit or relevance.

Classifying free-text triage chief complaints into syndromic categories with natural language processing.

PubMed

Chapman, Wendy W; Christensen, Lee M; Wagner, Michael M; Haug, Peter J; Ivanov, Oleg; Dowling, John N; Olszewski, Robert T

2005-01-01

Develop and evaluate a natural language processing application for classifying chief complaints into syndromic categories for syndromic surveillance. Much of the input data for artificial intelligence applications in the medical field are free-text patient medical records, including dictated medical reports and triage chief complaints. To be useful for automated systems, the free-text must be translated into encoded form. We implemented a biosurveillance detection system from Pennsylvania to monitor the 2002 Winter Olympic Games. Because input data was in free-text format, we used a natural language processing text classifier to automatically classify free-text triage chief complaints into syndromic categories used by the biosurveillance system. The classifier was trained on 4700 chief complaints from Pennsylvania. We evaluated the ability of the classifier to classify free-text chief complaints into syndromic categories with a test set of 800 chief complaints from Utah. The classifier produced the following areas under the ROC curve: Constitutional = 0.95; Gastrointestinal = 0.97; Hemorrhagic = 0.99; Neurological = 0.96; Rash = 1.0; Respiratory = 0.99; Other = 0.96. Using information stored in the system's semantic model, we extracted from the Respiratory classifications lower respiratory complaints and lower respiratory complaints with fever with a precision of 0.97 and 0.96, respectively. Results suggest that a trainable natural language processing text classifier can accurately extract data from free-text chief complaints for biosurveillance.

A Technique for Machine-Aided Indexing

ERIC Educational Resources Information Center

Klingbiel, Paul H.

1973-01-01

The technique for machine-aided indexing developed at the Defense Documentation Center (DDC) is illustrated on a randomly chosen abstract. Additional text is provided in coded form so that the reader can more fully explore this technique. (2 references) (Author)

Medical Subject Headings (MeSH) for indexing and retrieving open-source healthcare data.

PubMed

Marc, David T; Khairat, Saif S

2014-01-01

The US federal government initiated the Open Government Directive where federal agencies are required to publish high value datasets so that they are available to the public. Data.gov and the community site Healthdata.gov were initiated to disperse such datasets. However, data searches and retrieval for these sites are keyword driven and severely limited in performance. The purpose of this paper is to address the issue of extracting relevant open-source data by proposing a method of adopting the MeSH framework for indexing and data retrieval. A pilot study was conducted to compare the performance of traditional keywords to MeSH terms for retrieving relevant open-source datasets related to "mortality". The MeSH framework resulted in greater sensitivity with comparable specificity to the keyword search. MeSH showed promise as a method for indexing and retrieving data, yet future research should conduct a larger scale evaluation of the performance of the MeSH framework for retrieving relevant open-source healthcare datasets.

Radiation Oncology in Undergraduate Medical Education: A Literature Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dennis, Kristopher E.B., E-mail: kdennis@bccancer.bc.c; Duncan, Graeme

2010-03-01

Purpose: To review the published literature pertaining to radiation oncology in undergraduate medical education. Methods and Materials: Ovid MEDLINE, Ovid MEDLINE Daily Update and EMBASE databases were searched for the 11-year period of January 1, 1998, through the last week of March 2009. A medical librarian used an extensive list of indexed subject headings and text words. Results: The search returned 640 article references, but only seven contained significant information pertaining to teaching radiation oncology to medical undergraduates. One article described a comprehensive oncology curriculum including recommended radiation oncology teaching objectives and sample student evaluations, two described integrating radiation oncologymore » teaching into a radiology rotation, two described multidisciplinary anatomy-based courses intended to reinforce principles of tumor biology and radiotherapy planning, one described an exercise designed to test clinical reasoning skills within radiation oncology cases, and one described a Web-based curriculum involving oncologic physics. Conclusions: To the authors' knowledge, this is the first review of the literature pertaining to teaching radiation oncology to medical undergraduates, and it demonstrates the paucity of published work in this area of medical education. Teaching radiation oncology should begin early in the undergraduate process, should be mandatory for all students, and should impart knowledge relevant to future general practitioners rather than detailed information relevant only to oncologists. Educators should make use of available model curricula and should integrate radiation oncology teaching into existing curricula or construct stand-alone oncology rotations where the principles of radiation oncology can be conveyed. Assessments of student knowledge and curriculum effectiveness are critical.« less

The Role of Reading Time Complexity and Reading Speed in Text Comprehension

ERIC Educational Resources Information Center

Wallot, Sebastian; O'Brien, Beth A.; Haussmann, Anna; Kloos, Heidi; Lyby, Marlene S.

2014-01-01

Reading speed is commonly used as an index of reading fluency. However, reading speed is not a consistent predictor of text comprehension, when speed and comprehension are measured on the same text within the same reader. This might be due to the somewhat ambiguous nature of reading speed, which is sometimes regarded as a feature of the reading…

Associations among medication regimen complexity, medical specialty, and medication possession ratio in newly diagnosed hypertensive patients

PubMed Central

Ho, Chen-Pei; Yeh, Jih-I; Wen, Shu-Hui; Lee, Tony Jer-Fu

2017-01-01

Abstract The aim of this study was to explore the associations among the medication regimen complexity index (MRCI), medical specialty, and medication possession ratio (MPR) in newly diagnosed hypertensive patients. Data from 19,859 newly diagnosed hypertensive patients were collected from 2,000,000 random samples of the National Health Insurance Research Database in Taiwan. All study participants were followed for 1 year after the first diagnosis of hypertension. MPR was defined as total days of antihypertensive drugs supplied/365 days. MRCI was calculated on the basis of the type of dosage forms, dosing frequency, and additional directions for use of antihypertensive drugs. Patients were further restricted to those who visited the same medical specialty to examine specialty-specific variations in the MRCI and MPR. The mean MPR was 54.83%, and the sample sizes for the low-, medium-, and high-MPR groups were 9806 (49.38%), 4619 (23.26%), and 5434 (27.36%), respectively. More than 50% of the patients visited the same medical specialty during the 1-year follow-up. The mean MRCI was 3.64; the cardiology specialty had the highest MRCI, and the family medicine specialty had the lowest. Multiple linear regression analyses showed that MRCI was negatively associated with MPR (β = −7.75, P ≤ .01) whether or not the patients visited the same medical specialty. For the patients who visited the same medical specialty, those treated by endocrinology and metabolism specialists had a significantly higher MPR (β = 9.87, P ≤ .01) than that of those treated by family medicine specialists. MRCI and medical specialty were both significantly associated with the MPR of newly diagnosed hypertensive patients. PMID:29137042

Medical Science and Research in Iran.

PubMed

Akhondzadeh, Shahin; Ebadifar, Asghar; Baradaran Eftekhari, Monir; Falahat, Katayoun

2017-11-01

During the last 3 decades, Iran has experienced a rapid population growth and at the same time the health of Iranian people has improved greatly. This achievement was mainly due to training and availability of health manpower, well organized public health network and medical science and research improvement. In this article, we aimed to report the relevant data about the medical science and research situation in Iran and compare them with other countries. In this study, after reviewing science development and research indicators in medical sciences with participation of key stakeholders, we selected 3 main hybrid indexes consisting of "Research and Development (R&D) expenditures," "Personnel in Science and Technology sector" and "knowledge generation" for evaluation of medical science and research situation. Data was extracted from reliable databases. Over the past decade, Iran has achieved significant success in medical sciences and for the first time in 2015 based on Scopus index, Iran ranked first in the number of published scientific papers and number of citations in the region and among all Islamic countries. Also, 2% of the world's publications belong to Iran. Regarding innovation, the number of Iranian patents submitted to the United States Patent and Trademark Office (USPTO) was 3 and 43 in 2008 and 2013, respectively. In these years, the number of personnel in science and technology sectors including post graduate students, researchers and academic members in universities of medical sciences (UMSs) have increased. The female students in medical sciences field account for about twothirds of all students. Also, women comprise about one-third of faculty members. Since 5 years ago, Iran has had growth in science and technology parks. These achievements were attained in spite of the fact that research spending in Iran was still very low (0.5% of gross domestic product [GDP]) due to economic hardships and sanctions. Medical science and research development has

From Paper to Practice; Indexing Systems and Ethical Standards.

PubMed

Astaneh, Behrooz; Masoumi, Sarah

2018-04-01

Currently one of the main goals of editors is to attain a higher visibility for their journals. On the other hand, authors strive to publish their research in journals indexed in eminent databases such as Scopus, Thompson Reuters' Web of Science (ISI), Medline, etc. Therefore, clarifying the standards of indexing is of great importance. One of the most important issues in publication is the ethical considerations, which are mainly described by organizations, such as the International Committee of Medical Journal Editors and the Committee on Publication Ethics. In this study, we examined the ethical requirements of high impact databases for indexing journals to investigate whether they mention or mandate journals to adhere to publication ethics. We found that only Scopus mandated journals to state clear ethical policies on their website as a criterion for being indexed while Medline and Directory of Open Access Journals advised journals to adhere to ethics, not mandated, and Web of Science (ISI) and PubMed Central made no mention of ethics as a required criterion for indexing. Based on this short review, there seems to be a gap between the requirements of indexing systems and international guidelines for publication ethics. Currently, most indexing systems have only partially recommended journals to consider ethical issues. In such an atmosphere, we cannot expect journals or as a result, authors to professionally, completely, and whole heartedly implement ethical guidelines as a mandatory rule in their journals and research, when the indexing systems that most editors want to be indexed in and most authors want to be cited in do not mandate such guidelines.

Study on index system of GPS interference effect evaluation

NASA Astrophysics Data System (ADS)

Zhang, Kun; Zeng, Fangling; Zhao, Yuan; Zeng, Ruiqi

2018-05-01

Satellite navigation interference effect evaluation is the key technology to break through the research of Navigation countermeasure. To evaluate accurately the interference degree and Anti-jamming ability of GPS receiver, this text based on the existing research results of Navigation interference effect evaluation, build the index system of GPS receiver effectiveness evaluation from four levels of signal acquisition, tracking, demodulation and positioning/timing and establish the model for each index. These indexes can accurately and quantitatively describe the interference effect at all levels.

Utilisation of helicopter emergency medical services in the early medical response to major incidents: a systematic literature review

PubMed Central

Johnsen, Anne Siri; Fattah, Sabina; Sollid, Stephen J M; Rehn, Marius

2016-01-01

Objective This systematic review identifies, describes and appraises the literature describing the utilisation of helicopter emergency medical services (HEMS) in the early medical response to major incidents. Setting Early prehospital phase of a major incident. Design Systematic literature review performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, the Web of Science, PsycINFO, Scopus, Cinahl, Bibsys Ask, Norart, Svemed and UpToDate were searched using phrases that combined HEMS and ‘major incidents’ to identify when and how HEMS was utilised. The identified studies were subjected to data extraction and appraisal. Results The database search identified 4948 articles. Based on the title and abstract, the full text of 96 articles was obtained; of these, 37 articles were included in the review, and an additional five were identified by searching the reference lists of the 37 articles. HEMS was used to transport medical and rescue personnel to the incident and to transport patients to the hospital, especially when the infrastructure was damaged. Insufficient air traffic control, weather conditions, inadequate landing sites and failing communication were described as challenging in some incidents. Conclusions HEMS was used mainly for patient treatment and to transport patients, personnel and equipment in the early medical management of major incidents, but the optimal utilisation of this specialised resource remains unclear. This review identified operational areas with improvement potential. A lack of systematic indexing, heterogeneous data reporting and weak methodological design, complicated the identification and comparison of incidents, and more systematic reporting is needed. Trial registration number CRD42013004473. PMID:26861938

Physician. A metapaedogogical text.

PubMed

Dean-Jones, Lesley

2010-01-01

It has generally been thought that the short treatise Physician was written for the beginning medical student and as such it has been criticized for being so superficial as to be worthless for producing anything but an empty charade of a physician. There are also numerous cruces in the text on which scholars have failed to come to any consensus. This paper argues that by taking the audience of the treatise to be the beginning instructor rather than the beginning student the tone of and information included in the treatise can be seen to be appropriate and the textual cruces can all be explained with little or no amendment by the same hypothesis.

Automated MeSH indexing of the World-Wide Web.

PubMed Central

Fowler, J.; Kouramajian, V.; Maram, S.; Devadhar, V.

1995-01-01

To facilitate networked discovery and information retrieval in the biomedical domain, we have designed a system for automatic assignment of Medical Subject Headings to documents retrieved from the World-Wide Web. Our prototype implementations show significant promise. We describe our methods and discuss the further development of a completely automated indexing tool called the "Web-MeSH Medibot." PMID:8563421

Subject Indexes vs. Original Documents as Research Sources: A Comparative Account of Text Construction and Use for Academic Libraries.

ERIC Educational Resources Information Center

Eichman, Thomas Lee

An adaptation of Heilprin's model of the path of propagation of human messages is used to explore the truism that more experienced academic researchers tend to go directly to the published literature, while less experienced researchers may rely more on such secondary sources as indexes and other library reference and bibliographic services. The…

TextHunter – A User Friendly Tool for Extracting Generic Concepts from Free Text in Clinical Research

PubMed Central

Jackson MSc, Richard G.; Ball, Michael; Patel, Rashmi; Hayes, Richard D.; Dobson, Richard J.B.; Stewart, Robert

2014-01-01

Observational research using data from electronic health records (EHR) is a rapidly growing area, which promises both increased sample size and data richness - therefore unprecedented study power. However, in many medical domains, large amounts of potentially valuable data are contained within the free text clinical narrative. Manually reviewing free text to obtain desired information is an inefficient use of researcher time and skill. Previous work has demonstrated the feasibility of applying Natural Language Processing (NLP) to extract information. However, in real world research environments, the demand for NLP skills outweighs supply, creating a bottleneck in the secondary exploitation of the EHR. To address this, we present TextHunter, a tool for the creation of training data, construction of concept extraction machine learning models and their application to documents. Using confidence thresholds to ensure high precision (>90%), we achieved recall measurements as high as 99% in real world use cases. PMID:25954379

Potential Limitations of E-mail and Text Messaging in Improving Adherence in Glaucoma and Ocular Hypertension.

PubMed

Saeedi, Osamah J; Luzuriaga, Christine; Ellish, Nancy; Robin, Alan

2015-01-01

To determine how receptive patients are to the use of e-mail and text message reminders for appointments and medications. We conducted a consecutive cross-sectional survey of eligible patients with glaucoma or ocular hypertension at a private glaucoma subspecialty practice with 3 locations from February 2011 to January 2012. Main outcome measures were answers to survey questions regarding how receptive patients are to e-mail and text messaging reminders for appointments and medications. Of 989 patients, 404 (40.8%) patients reported that e-mail reminders would help remember appointments and 185 (18.7%) reported that they would help for medications. Among those with access to text messaging, 280 (68.9%) reported text messaging would help them remember appointments and 193 (47.5%) reported it would help with medications. Patients who reported e-mail would help them remember medications were more likely to live in an urban location [P=0.05, odds ratio (OR)=1.84], check the internet at least daily (P≤0.001, OR=1.04), check e-mail when not at home or the office (P=0.02, OR=1.62), and know how to open attachments (P=0.03, OR=1.87). Patients who reported that text messaging would help them remember their medications were more likely to be 40 or less (P≤0.001, OR=8.54) and African American (P<0.001, OR=2.59). E-mail and text messaging reminders currently may have a limited utility in improving adherence in the general glaucoma population but may be useful in younger patients with glaucoma.

Patients' perspectives on the medical primary-secondary care interface: systematic review and synthesis of qualitative research.

PubMed

Sampson, Rod; Cooper, Jamie; Barbour, Rosaline; Polson, Rob; Wilson, Philip

2015-10-15

To synthesise the published literature on the patient experience of the medical primary-secondary care interface and to determine priorities for future work in this field aimed at improving clinical outcomes. Systematic review and metaethnographic synthesis of primary studies that used qualitative methods to explore patients' perspectives of the medical primary-secondary care interface. International primary-secondary care interface. EMBASE, MEDLINE, CINAHL Plus with Full text, PsycINFO, Psychology and Behavioural Sciences Collection, Health Business Elite, Biomedica Reference Collection: Comprehensive Library, Information Science & Technology Abstracts, eBook Collection, Web of Science Core Collection: Citation Indexes and Social Sciences Citation Index, and grey literature. Studies were eligible for inclusion if they were full research papers employing qualitative methodology to explore patients' perspectives of the medical primary-secondary care interface. The 7-step metaethnographic approach described by Noblit and Hare, which involves cross-interpretation between studies while preserving the context of the primary data. The search identified 690 articles, of which 39 were selected for full-text review. 20 articles were included in the systematic review that encompassed a total of 689 patients from 10 countries. 4 important areas specific to the primary-secondary care interface from the patients' perspective emerged: barriers to care, communication, coordination, and 'relationships and personal value'. Patients should be the focus of any transfer of care between primary and secondary systems. From their perspective, areas for improvement may be classified into four domains that should usefully guide future work aimed at improving quality at this important interface. PROSPERO CRD42014009486. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Medical Named Entity Recognition for Indonesian Language Using Word Representations

NASA Astrophysics Data System (ADS)

Rahman, Arief

2018-03-01

Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.

Analysis of development levels in the cities of Tehran province regarding health infrastructural index: the strategy of standardized score and Morris' inequality index.

PubMed

Javani, Ali; Abolhallaje, Masoud; Raadabadi, Mehdi; Rezaee Dehaghi, Hanieh; Nazari, Aslan; Nazari, Hamed; Chatrouz, Azadeh

2015-01-01

One of the main indexes of development is health index or the degree to which a society enjoys health and therapeutic services. The present study was done with the aim to analyze development levels in cities in Tehran regarding health infrastructural index using the standardized score and Morris' model. This is a descriptive and pragmatic study which ranks 14 cities in Tehran province using the standardized score and Morris' models based on 10 selected health indexes. The required data were gathered using a researcher-made information list and the information gathered from the Statistics Center and Tehran University of Medical Sciences. The data were analyzed using Excel software. The development coefficient in the studied cities varies from 0.595 to -0.379 so that Rey city has the highest level of development and Pishva city has the lowest level of development among the studied cities. The more number of the cities (43%) was among the rather undeveloped group and none of the cities (0%) was in the rather developed group. Regarding the findings, there is a big gap and difference regarding enjoying health and therapeutic infrastructural indexes among the cities in Tehran province. Therefore, it is suggested that development-oriented plans consistentent with development levels should be implemented in these cities.

A systematic review of patient medication error on self-administering medication at home.

PubMed

Mira, José Joaquín; Lorenzo, Susana; Guilabert, Mercedes; Navarro, Isabel; Pérez-Jover, Virtudes

2015-06-01

Medication errors have been analyzed as a health professionals' responsibility (due to mistakes in prescription, preparation or dispensing). However, sometimes, patients themselves (or their caregivers) make mistakes in the administration of the medication. The epidemiology of patient medication errors (PEs) has been scarcely reviewed in spite of its impact on people, on therapeutic effectiveness and on incremental cost for the health systems. This study reviews and describes the methodological approaches and results of published studies on the frequency, causes and consequences of medication errors committed by patients at home. A review of research articles published between 1990 and 2014 was carried out using MEDLINE, Web-of-Knowledge, Scopus, Tripdatabase and Index Medicus. The frequency of PE was situated between 19 and 59%. The elderly and the preschooler population constituted a higher number of mistakes than others. The most common were: incorrect dosage, forgetting, mixing up medications, failing to recall indications and taking out-of-date or inappropriately stored drugs. The majority of these mistakes have no negative consequences. Health literacy, information and communication and complexity of use of dispensing devices were identified as causes of PEs. Apps and other new technologies offer several opportunities for improving drug safety.

Context-sensitive medical information retrieval.

PubMed

Auerbuch, Mordechai; Karson, Tom H; Ben-Ami, Benjamin; Maimon, Oded; Rokach, Lior

2004-01-01

Substantial medical data such as pathology reports, operative reports, discharge summaries, and radiology reports are stored in textual form. Databases containing free-text medical narratives often need to be searched to find relevant information for clinical and research purposes. Terms that appear in these documents tend to appear in different contexts. The con-text of negation, a negative finding, is of special importance, since many of the most frequently described findings are those denied by the patient or subsequently "ruled out." Hence, when searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the retrieved documents will be irrelevant. The purpose of this work is to develop a methodology for automated learning of negative context patterns in medical narratives and test the effect of context identification on the performance of medical information retrieval. The algorithm presented significantly improves the performance of information retrieval done on medical narratives. The precision im-proves from about 60%, when using context-insensitive retrieval, to nearly 100%. The impact on recall is only minor. In addition, context-sensitive queries enable the user to search for terms in ways not otherwise available

Computer-Based Medical System

NASA Technical Reports Server (NTRS)

1998-01-01

SYMED, Inc., developed a unique electronic medical records and information management system. The S2000 Medical Interactive Care System (MICS) incorporates both a comprehensive and interactive medical care support capability and an extensive array of digital medical reference materials in either text or high resolution graphic form. The system was designed, in cooperation with NASA, to improve the effectiveness and efficiency of physician practices. The S2000 is a MS (Microsoft) Windows based software product which combines electronic forms, medical documents, records management, and features a comprehensive medical information system for medical diagnostic support and treatment. SYMED, Inc. offers access to its medical systems to all companies seeking competitive advantages.

Neural network based chemical structure indexing.

PubMed

Rughooputh, S D; Rughooputh, H C

2001-01-01

Searches on chemical databases are presently dominated by the text-based content of a paper which can be indexed into a keyword searchable form. Such traditional searches can prove to be very time-consuming and discouraging to the less frequent scientist. We report a simple chemical indexing based on the molecular structure alone. The method used is based on a one-to-one correspondence between the chemical structure presented as an image to a neural network and the corresponding binary output. The method is direct and less cumbersome (compared with traditional methods) and proves to be robust, elegant, and very versatile.

Trends of E-Learning Research from 2000 to 2008: Use of Text Mining and Bibliometrics

ERIC Educational Resources Information Center

Hung, Jui-long

2012-01-01

This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…

Medical theses as part of the scientific training in basic medical and dental education: experiences from Finland

PubMed Central

Nieminen, Pentti; Sipilä, Kirsi; Takkinen, Hanna-Mari; Renko, Marjo; Risteli, Leila

2007-01-01

Background Teaching the principles of scientific research in a comprehensive way is important at medical and dental schools. In many countries medical and dental training is not complete until the candidate has presented a diploma thesis. The objective of this study was to evaluate the nature, quality, publication pattern and visibility of Finnish medical diploma theses. Methods A total of 256 diploma theses presented at the University of Oulu from 2001 to 2003 were analysed. Using a standardised questionnaire, we extracted several characteristics from each thesis. We used the name of the student to assess whether the thesis resulted in a scientific publication indexed in medical article databases. The number of citations received by each published thesis was also recorded. Results A high proportion of the theses (69.5%) were essentially statistical in character, often combined with an extensive literature review or the development of a laboratory method. Most of them were supervised by clinical departments (55.9%). Only 61 theses (23.8%) had been published in indexed scientific journals. Theses in the fields of biomedicine and diagnostics were published in more widely cited journals. The median number of citations received per year was 2.7 and the range from 0 to 14.7. Conclusion The theses were seldom written according to the principles of scientific communication and the proportion of actually published was small. The visibility of these theses and their dissemination to the scientific community should be improved. PMID:18053247

Medical theses as part of the scientific training in basic medical and dental education: experiences from Finland.

PubMed

Nieminen, Pentti; Sipilä, Kirsi; Takkinen, Hanna-Mari; Renko, Marjo; Risteli, Leila

2007-12-05

Teaching the principles of scientific research in a comprehensive way is important at medical and dental schools. In many countries medical and dental training is not complete until the candidate has presented a diploma thesis. The objective of this study was to evaluate the nature, quality, publication pattern and visibility of Finnish medical diploma theses. A total of 256 diploma theses presented at the University of Oulu from 2001 to 2003 were analysed. Using a standardised questionnaire, we extracted several characteristics from each thesis. We used the name of the student to assess whether the thesis resulted in a scientific publication indexed in medical article databases. The number of citations received by each published thesis was also recorded. A high proportion of the theses (69.5%) were essentially statistical in character, often combined with an extensive literature review or the development of a laboratory method. Most of them were supervised by clinical departments (55.9%). Only 61 theses (23.8%) had been published in indexed scientific journals. Theses in the fields of biomedicine and diagnostics were published in more widely cited journals. The median number of citations received per year was 2.7 and the range from 0 to 14.7. The theses were seldom written according to the principles of scientific communication and the proportion of actually published was small. The visibility of these theses and their dissemination to the scientific community should be improved.

Development of a personalized bidirectional text messaging tool for HIV adherence assessment and intervention among substance abusers.

PubMed

Ingersoll, Karen; Dillingham, Rebecca; Reynolds, George; Hettema, Jennifer; Freeman, Jason; Hosseinbor, Sharzad; Winstead-Derlega, Chris

2014-01-01

We describe the development of a two-way text messaging intervention tool for substance users who are non-adherent with HIV medications, and examine message flow data for feasibility and acceptability. The assessment and intervention tool, TxText, is fully automated, sending participants mood, substance use, and medication adherence queries by text message. Participants respond, the tool recognizes the category of response, and sends the personalized intervention message that participants designed in return. In 10months, the tool sent 16,547 messages (half initial, half follow-up) to 31 participants assigned to the TxText condition, who sent 6711 messages in response to the initial messages. Response rates to substance use (n=2370), medication (n=2918) and mood (n=4639) queries were 67, 69, and 64%, respectively. Responses indicating medication adherence, abstinence from substances, and good moods were more common than negative responses. The TxText tool can send messages daily over a 3month period, receive responses, and decode them to deliver personalized affirming or intervention messages. While we await the outcomes of a pilot randomized trial, the process analysis shows that TxText is acceptable and feasible for substance abusers with HIV, and may serve as a complement to HIV medical care. © 2013.

Development of a Personalized Bidirectional Text Messaging Tool for HIV Adherence Assessment and Intervention among Substance Abusers

PubMed Central

Ingersoll, Karen; Dillingham, Rebecca; Reynolds, George; Hettema, Jennifer; Freeman, Jason; Hosseinbor, Sharzad; Winstead-Derlega, Chris

2013-01-01

We describe the development of a two-way text messaging intervention tool for substance users who are non-adherent with HIV medications, and examine message flow data for feasibility and acceptability. The assessment and intervention tool, TxText, is fully automated, sending participants mood, substance use, and medication adherence queries by text message. Participants respond, the tool recognizes the category of response, and sends the personalized intervention message that participants designed in return. In 10 months, the tool sent 16,547 messages (half initial, half follow-up) to 31 participants assigned to the TxText condition, who sent 6711 messages in response to the initial messages. Response rates to substance use (n=2370), medication (n=2918) and mood (n=4639) queries were 67%, 69%, and 64%, respectively. Responses indicating medication adherence, abstinence from substances, and good moods were more common than negative responses. The TxText tool can send messages daily over a 3 month period, receive responses, and decode them to deliver personalized affirming or intervention messages. While we await the outcomes of a pilot randomized trial, the process analysis shows that TxText is acceptable and feasible for substance abusers with HIV, and may serve as a complement to HIV medical care. PMID:24029625

The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction.

PubMed

Najafi, Elham; Darooneh, Amir H

2015-01-01

A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction.

The Fractal Patterns of Words in a Text: A Method for Automatic Keyword Extraction

PubMed Central

Najafi, Elham; Darooneh, Amir H.

2015-01-01

A text can be considered as a one dimensional array of words. The locations of each word type in this array form a fractal pattern with certain fractal dimension. We observe that important words responsible for conveying the meaning of a text have dimensions considerably different from one, while the fractal dimensions of unimportant words are close to one. We introduce an index quantifying the importance of the words in a given text using their fractal dimensions and then ranking them according to their importance. This index measures the difference between the fractal pattern of a word in the original text relative to a shuffled version. Because the shuffled text is meaningless (i.e., words have no importance), the difference between the original and shuffled text can be used to ascertain degree of fractality. The degree of fractality may be used for automatic keyword detection. Words with the degree of fractality higher than a threshold value are assumed to be the retrieved keywords of the text. We measure the efficiency of our method for keywords extraction, making a comparison between our proposed method and two other well-known methods of automatic keyword extraction. PMID:26091207

Effects of Changes in Number of Medications and Drug Burden Index Exposure on Transitions Between Frailty States and Death: The Concord Health and Ageing in Men Project Cohort Study.

PubMed

Jamsen, Kris M; Bell, J Simon; Hilmer, Sarah N; Kirkpatrick, Carl M J; Ilomäki, Jenni; Le Couteur, David; Blyth, Fiona M; Handelsman, David J; Waite, Louise; Naganathan, Vasi; Cumming, Robert G; Gnjidic, Danijela

2016-01-01

To investigate the effects of number of medications and Drug Burden Index (DBI) on transitions between frailty stages and death in community-dwelling older men. Cohort study. Sydney, Australia. Community-dwelling men aged 70 and older (N=1,705). Self-reported questionnaires and clinic visits were conducted at baseline and 2 and 5 years. Frailty was assessed at all three waves according to the modified Fried frailty phenotype. The total number of regular prescription medications and DBI (a measure of exposure to sedative and anticholinergic medications) were calculated over the three waves. Data on mortality over 9 years were obtained. Multistate modeling was used to characterize the transitions across three frailty states (robust, prefrail, frail) and death. Each additional medication was associated with a 22% greater risk of transitioning from the robust state to death (adjusted 95% confidence interval (CI)=1.06-1.41). Every unit increase in DBI was associated with a 73% greater risk of transitioning from the robust state to the prefrail state (adjusted 95% CI=1.30-2.31) and a 2.75 times greater risk of transitioning from the robust state to death (adjusted 95% CI=1.60-4.75). There was no evidence of an adjusted association between total number of medications or DBI and the other transitions. Although the possibility of confounding by indication cannot be excluded, additional medications were associated with greater risk of mortality in robust community-dwelling older men. Greater DBI was also associated with greater risk of death and transitioning from the robust state to the prefrail state. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

Developing a comprehensive system for content-based retrieval of image and text data from a national survey

NASA Astrophysics Data System (ADS)

Antani, Sameer K.; Natarajan, Mukil; Long, Jonathan L.; Long, L. Rodney; Thoma, George R.

2005-04-01

The article describes the status of our ongoing R&D at the U.S. National Library of Medicine (NLM) towards the development of an advanced multimedia database biomedical information system that supports content-based image retrieval (CBIR). NLM maintains a collection of 17,000 digitized spinal X-rays along with text survey data from the Second National Health and Nutritional Examination Survey (NHANES II). These data serve as a rich data source for epidemiologists and researchers of osteoarthritis and musculoskeletal diseases. It is currently possible to access these through text keyword queries using our Web-based Medical Information Retrieval System (WebMIRS). CBIR methods developed specifically for biomedical images could offer direct visual searching of these images by means of example image or user sketch. We are building a system which supports hybrid queries that have text and image-content components. R&D goals include developing algorithms for robust image segmentation for localizing and identifying relevant anatomy, labeling the segmented anatomy based on its pathology, developing suitable indexing and similarity matching methods for images and image features, and associating the survey text information for query and retrieval along with the image data. Some highlights of the system developed in MATLAB and Java are: use of a networked or local centralized database for text and image data; flexibility to incorporate new research work; provides a means to control access to system components under development; and use of XML for structured reporting. The article details the design, features, and algorithms in this third revision of this prototype system, CBIR3.

Evaluation of natural language processing from emergency department computerized medical records for intra-hospital syndromic surveillance

PubMed Central

2011-01-01

Background The identification of patients who pose an epidemic hazard when they are admitted to a health facility plays a role in preventing the risk of hospital acquired infection. An automated clinical decision support system to detect suspected cases, based on the principle of syndromic surveillance, is being developed at the University of Lyon's Hôpital de la Croix-Rousse. This tool will analyse structured data and narrative reports from computerized emergency department (ED) medical records. The first step consists of developing an application (UrgIndex) which automatically extracts and encodes information found in narrative reports. The purpose of the present article is to describe and evaluate this natural language processing system. Methods Narrative reports have to be pre-processed before utilizing the French-language medical multi-terminology indexer (ECMT) for standardized encoding. UrgIndex identifies and excludes syntagmas containing a negation and replaces non-standard terms (abbreviations, acronyms, spelling errors...). Then, the phrases are sent to the ECMT through an Internet connection. The indexer's reply, based on Extensible Markup Language, returns codes and literals corresponding to the concepts found in phrases. UrgIndex filters codes corresponding to suspected infections. Recall is defined as the number of relevant processed medical concepts divided by the number of concepts evaluated (coded manually by the medical epidemiologist). Precision is defined as the number of relevant processed concepts divided by the number of concepts proposed by UrgIndex. Recall and precision were assessed for respiratory and cutaneous syndromes. Results Evaluation of 1,674 processed medical concepts contained in 100 ED medical records (50 for respiratory syndromes and 50 for cutaneous syndromes) showed an overall recall of 85.8% (95% CI: 84.1-87.3). Recall varied from 84.5% for respiratory syndromes to 87.0% for cutaneous syndromes. The most frequent cause of

Text mining applications in psychiatry: a systematic literature review.

PubMed

Abbe, Adeline; Grouin, Cyril; Zweigenbaum, Pierre; Falissard, Bruno

2016-06-01

The expansion of biomedical literature is creating the need for efficient tools to keep pace with increasing volumes of information. Text mining (TM) approaches are becoming essential to facilitate the automated extraction of useful biomedical information from unstructured text. We reviewed the applications of TM in psychiatry, and explored its advantages and limitations. A systematic review of the literature was carried out using the CINAHL, Medline, EMBASE, PsycINFO and Cochrane databases. In this review, 1103 papers were screened, and 38 were included as applications of TM in psychiatric research. Using TM and content analysis, we identified four major areas of application: (1) Psychopathology (i.e. observational studies focusing on mental illnesses) (2) the Patient perspective (i.e. patients' thoughts and opinions), (3) Medical records (i.e. safety issues, quality of care and description of treatments), and (4) Medical literature (i.e. identification of new scientific information in the literature). The information sources were qualitative studies, Internet postings, medical records and biomedical literature. Our work demonstrates that TM can contribute to complex research tasks in psychiatry. We discuss the benefits, limits, and further applications of this tool in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Understanding Medication Schedules: Do Pictograms Help?

PubMed

Leong, Madeline; Tam, Vernissia; Xu, Timothy; Peters, Matthew

2018-06-01

Previous studies suggest that pictograms may improve patients' understanding of medication schedules. Understanding a medication schedule is a necessary first step for medication adherence. This study aimed to determine if pictograms improved patients' ability to correctly fill a pillbox. This is a randomized, controlled, crossover pilot study. This study involves 30 patients on the medical wards of an urban, tertiary care center. The PillBox Test required participants to fill a 7-day pillbox with pill-sized colored beads. Participants were randomized to either the control or the experimental condition first. In the control condition, a standard pillbox was used with text instructions on the pill bottles. In the experimental condition, a pictogram pillbox was used with text and pictogram instructions on the pill bottles. There was no significant difference in passing on text or pictogram PillBox Test based on the order of group administration. However, 77% of participants reported that pictograms helped them understand medication instructions, 67% of participants preferred pictograms, and 93% felt pictograms should be used on all medication labels. In this pilot study, the use of pictograms did not significantly improve participants' ability to correctly fill a pillbox. However, most participants preferred pictograms to text labels. Further research is needed to determine the efficacy of pictograms in specific populations.

Medical Image Retrieval: A Multimodal Approach

PubMed Central

Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

2014-01-01

Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system. PMID:26309389

“Free Full Text Articles”: Where to Search for Them?

PubMed Central

Singh, Ashish; Singh, Manish; Singh, Ajai Kumar; Singh, Deepti; Singh, Pratibha; Sharma, Abhishek

2011-01-01

References form the backbone of any medical literature. Presently, because of high inflation, it is very difficult for any library/organization/college to purchase all journals. The condition is even worse for an individual person, such as private practitioners. The solution lies in the free availability of full-text articles. Here, the authors share their experiences about the accessibility of free full-text articles. PMID:22223965

Generalized entropies and the similarity of texts

NASA Astrophysics Data System (ADS)

Altmann, Eduardo G.; Dias, Laércio; Gerlach, Martin

2017-01-01

We show how generalized Gibbs-Shannon entropies can provide new insights on the statistical properties of texts. The universal distribution of word frequencies (Zipf’s law) implies that the generalized entropies, computed at the word level, are dominated by words in a specific range of frequencies. Here we show that this is the case not only for the generalized entropies but also for the generalized (Jensen-Shannon) divergences, used to compute the similarity between different texts. This finding allows us to identify the contribution of specific words (and word frequencies) for the different generalized entropies and also to estimate the size of the databases needed to obtain a reliable estimation of the divergences. We test our results in large databases of books (from the google n-gram database) and scientific papers (indexed by Web of Science).

Prediction of body mass index status from voice signals based on machine learning for automated medical applications.

PubMed

Lee, Bum Ju; Kim, Keun Ho; Ku, Boncho; Jang, Jun-Su; Kim, Jong Yeol

2013-05-01

The body mass index (BMI) provides essential medical information related to body weight for the treatment and prognosis prediction of diseases such as cardiovascular disease, diabetes, and stroke. We propose a method for the prediction of normal, overweight, and obese classes based only on the combination of voice features that are associated with BMI status, independently of weight and height measurements. A total of 1568 subjects were divided into 4 groups according to age and gender differences. We performed statistical analyses by analysis of variance (ANOVA) and Scheffe test to find significant features in each group. We predicted BMI status (normal, overweight, and obese) by a logistic regression algorithm and two ensemble classification algorithms (bagging and random forests) based on statistically significant features. In the Female-2030 group (females aged 20-40 years), classification experiments using an imbalanced (original) data set gave area under the receiver operating characteristic curve (AUC) values of 0.569-0.731 by logistic regression, whereas experiments using a balanced data set gave AUC values of 0.893-0.994 by random forests. AUC values in Female-4050 (females aged 41-60 years), Male-2030 (males aged 20-40 years), and Male-4050 (males aged 41-60 years) groups by logistic regression in imbalanced data were 0.585-0.654, 0.581-0.614, and 0.557-0.653, respectively. AUC values in Female-4050, Male-2030, and Male-4050 groups in balanced data were 0.629-0.893 by bagging, 0.707-0.916 by random forests, and 0.695-0.854 by bagging, respectively. In each group, we found discriminatory features showing statistical differences among normal, overweight, and obese classes. The results showed that the classification models built by logistic regression in imbalanced data were better than those built by the other two algorithms, and significant features differed according to age and gender groups. Our results could support the development of BMI diagnosis

The MEDIGATE graphical user interface for entry of physical findings: design principles and implementation. Medical Examination Direct Iconic and Graphic Augmented Text Entry System.

PubMed

Yoder, J W; Schultz, D F; Williams, B T

1998-10-01

The solution to many of the problems of the computer-based recording of the medical record has been elusive, largely due to difficulties in the capture of those data elements that comprise the records of the Present Illness and of the Physical Findings. Reliable input of data has proven to be more complex than originally envisioned by early work in the field. This has led to more research and development into better data collection protocols and easy to use human-computer interfaces as support tools. The Medical Examination Direct Iconic and Graphic Augmented Text Entry System (MEDIGATE System) is a computer enhanced interactive graphic and textual record of the findings from physical examinations designed to provide ease of user input and to support organization and processing of the data characterizing these findings. The primary design objective of the MEDIGATE System is to develop and evaluate different interface designs for recording observations from the physical examination in an attempt to overcome some of the deficiencies in this major component of the individual record of health and illness.

The Body of the Text: Literacy's Corporeal Constant.

ERIC Educational Resources Information Center

Marvin, Carolyn

1994-01-01

Considers the role of bodily routines and practices as a component in the study of literacy. Examines a practice by physicians in the late 19th and early 20th centuries of binding fine or rare texts in human skin. Relates this embodied literacy practice to the transformation of medical practice from an oral to a textual discipline. (SR)

Medical conditions with neuropsychiatric manifestations.

PubMed

Isaac, Margaret L; Larson, Eric B

2014-09-01

Medical disease sometimes affects patients through neuropsychiatric manifestations. When neuropsychiatric symptoms are predominant, identifying medical disease early in the illness course is imperative because many of these conditions are reversible with appropriate treatment. A high index of suspicion is required on the part of clinicians, particularly when patients also present with physical signs or unexplained symptoms that might suggest a broader, systemic process. The processes that most commonly cause neuropsychiatric symptoms include infectious, autoimmune, endocrinologic, metabolic, and neoplastic diseases. This article focuses on the most common of these conditions, and conditions for which early diagnosis and treatment are particularly important. Copyright © 2014 Elsevier Inc. All rights reserved.